diff --git a/packages/kbot/dist-in/data/openai_models.json b/packages/kbot/dist-in/data/openai_models.json index 62c6ca5a..c0ad756a 100644 --- a/packages/kbot/dist-in/data/openai_models.json +++ b/packages/kbot/dist-in/data/openai_models.json @@ -1,5 +1,5 @@ { - "timestamp": 1767165092218, + "timestamp": 1769293001025, "models": [ { "id": "gpt-4-0613", @@ -20,15 +20,9 @@ "owned_by": "openai" }, { - "id": "chatgpt-image-latest", + "id": "gpt-5.2-codex", "object": "model", - "created": 1765925279, - "owned_by": "system" - }, - { - "id": "gpt-4o-mini-tts-2025-03-20", - "object": "model", - "created": 1765610731, + "created": 1766164985, "owned_by": "system" }, { @@ -49,6 +43,12 @@ "created": 1765760008, "owned_by": "system" }, + { + "id": "chatgpt-image-latest", + "object": "model", + "created": 1765925279, + "owned_by": "system" + }, { "id": "davinci-002", "object": "model", @@ -661,6 +661,12 @@ "created": 1765610545, "owned_by": "system" }, + { + "id": "gpt-4o-mini-tts-2025-03-20", + "object": "model", + "created": 1765610731, + "owned_by": "system" + }, { "id": "gpt-3.5-turbo-16k", "object": "model", diff --git a/packages/kbot/dist-in/data/openrouter_models.json b/packages/kbot/dist-in/data/openrouter_models.json index 0006bfe7..b3b2ac60 100644 --- a/packages/kbot/dist-in/data/openrouter_models.json +++ b/packages/kbot/dist-in/data/openrouter_models.json @@ -1,120 +1,14 @@ { - "timestamp": 1767165092339, + "timestamp": 1769293001166, "models": [ { - "id": "bytedance-seed/seed-1.6-flash", - "canonical_slug": "bytedance-seed/seed-1.6-flash-20250625", + "id": "minimax/minimax-m2-her", + "canonical_slug": "minimax/minimax-m2-her-20260123", "hugging_face_id": "", - "name": "ByteDance Seed: Seed 1.6 Flash", - "created": 1766505011, - "description": "Seed 1.6 Flash is an ultra-fast multimodal deep thinking model by ByteDance Seed, supporting both text and visual understanding. 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Learn more about using reasoning_details to pass back reasoning in our [docs](https://openrouter.ai/docs/use-cases/reasoning-tokens#preserving-reasoning-blocks).", - "context_length": 204800, + "name": "MiniMax: MiniMax M2-her", + "created": 1769177239, + "description": "MiniMax M2-her is a dialogue-first large language model built for immersive roleplay, character-driven chat, and expressive multi-turn conversations. 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It incorporates multimodal capabilities and adaptive deep thinking with a 256K context window.", + "context_length": 262144, + "architecture": { + "modality": "text+image+video->text", + "input_modalities": [ + "image", + "text", + "video" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Other", + "instruct_type": null + }, + "pricing": { + "prompt": "0.00000025", + "completion": "0.000002", + "request": "0", + "image": "0", + "web_search": "0", + "internal_reasoning": "0", + "input_cache_read": "0", + "input_cache_write": "0" + }, + "top_provider": { + "context_length": 262144, + "max_completion_tokens": 32768, + "is_moderated": false + }, + "per_request_limits": null, + "supported_parameters": [ + "frequency_penalty", + "include_reasoning", + "max_tokens", + "reasoning", + "response_format", + "stop", + "structured_outputs", + "temperature", + "tool_choice", + "tools", + "top_p" + ], + "default_parameters": { + "temperature": null, + "top_p": null, + "frequency_penalty": null + }, + "expiration_date": null + }, + { + "id": "minimax/minimax-m2.1", + "canonical_slug": "minimax/minimax-m2.1", + "hugging_face_id": "MiniMaxAI/MiniMax-M2.1", + "name": "MiniMax: MiniMax M2.1", + "created": 1766454997, + "description": "MiniMax-M2.1 is a lightweight, state-of-the-art large language model optimized for coding, agentic workflows, and modern application development. With only 10 billion activated parameters, it delivers a major jump in real-world capability while maintaining exceptional latency, scalability, and cost efficiency.\n\nCompared to its predecessor, M2.1 delivers cleaner, more concise outputs and faster perceived response times. It shows leading multilingual coding performance across major systems and application languages, achieving 49.4% on Multi-SWE-Bench and 72.5% on SWE-Bench Multilingual, and serves as a versatile agent “brain” for IDEs, coding tools, and general-purpose assistance.\n\nTo avoid degrading this model's performance, MiniMax highly recommends preserving reasoning between turns. Learn more about using reasoning_details to pass back reasoning in our [docs](https://openrouter.ai/docs/use-cases/reasoning-tokens#preserving-reasoning-blocks).", + "context_length": 196608, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Other", + "instruct_type": null + }, + "pricing": { + "prompt": "0.00000027", + "completion": "0.0000011" + }, + "top_provider": { + "context_length": 196608, + "max_completion_tokens": 196608, + "is_moderated": false + }, + "per_request_limits": null, "supported_parameters": [ "frequency_penalty", "include_reasoning", "logit_bias", "logprobs", "max_tokens", + "min_p", "presence_penalty", "reasoning", "repetition_penalty", @@ -166,7 +692,8 @@ "temperature": 1, "top_p": 0.9, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "z-ai/glm-4.7", @@ -205,6 +732,7 @@ "frequency_penalty", "include_reasoning", "logit_bias", + "logprobs", "max_tokens", "min_p", "presence_penalty", @@ -217,14 +745,17 @@ "temperature", "tool_choice", "tools", + "top_a", "top_k", + "top_logprobs", "top_p" ], "default_parameters": { "temperature": 1, "top_p": 0.95, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "google/gemini-3-flash-preview", @@ -235,7 +766,7 @@ "description": "Gemini 3 Flash Preview is a high speed, high value thinking model designed for agentic workflows, multi turn chat, and coding assistance. It delivers near Pro level reasoning and tool use performance with substantially lower latency than larger Gemini variants, making it well suited for interactive development, long running agent loops, and collaborative coding tasks. Compared to Gemini 2.5 Flash, it provides broad quality improvements across reasoning, multimodal understanding, and reliability.\n\nThe model supports a 1M token context window and multimodal inputs including text, images, audio, video, and PDFs, with text output. It includes configurable reasoning via thinking levels (minimal, low, medium, high), structured output, tool use, and automatic context caching. Gemini 3 Flash Preview is optimized for users who want strong reasoning and agentic behavior without the cost or latency of full scale frontier models.", "context_length": 1048576, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file+audio+video->text", "input_modalities": [ "text", "image", @@ -252,12 +783,11 @@ "pricing": { "prompt": "0.0000005", "completion": "0.000003", - "request": "0", - "image": "0", + "image": "0.0000005", "audio": "0.000001", - "web_search": "0", - "internal_reasoning": "0", - "input_cache_read": "0.00000005" + "internal_reasoning": "0.000003", + "input_cache_read": "0.00000005", + "input_cache_write": "0.00000008333333333333334" }, "top_provider": { "context_length": 1048576, @@ -282,7 +812,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "mistralai/mistral-small-creative", @@ -305,11 +836,7 @@ }, "pricing": { "prompt": "0.0000001", - "completion": "0.0000003", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.0000003" }, "top_provider": { "context_length": 32768, @@ -325,13 +852,14 @@ "temperature": 0.3, "top_p": 0.95, "frequency_penalty": null - } + }, + "expiration_date": null }, { - "id": "allenai/olmo-3.1-32b-think:free", + "id": "allenai/olmo-3.1-32b-think", "canonical_slug": "allenai/olmo-3.1-32b-think-20251215", "hugging_face_id": "allenai/Olmo-3.1-32B-Think", - "name": "AllenAI: Olmo 3.1 32B Think (free)", + "name": "AllenAI: Olmo 3.1 32B Think", "created": 1765907719, "description": "Olmo 3.1 32B Think is a large-scale, 32-billion-parameter model designed for deep reasoning, complex multi-step logic, and advanced instruction following. Building on the Olmo 3 series, version 3.1 delivers refined reasoning behavior and stronger performance across demanding evaluations and nuanced conversational tasks. Developed by Ai2 under the Apache 2.0 license, Olmo 3.1 32B Think continues the Olmo initiative’s commitment to openness, providing full transparency across model weights, code, and training methodology.", "context_length": 65536, @@ -347,8 +875,8 @@ "instruct_type": null }, "pricing": { - "prompt": "0", - "completion": "0", + "prompt": "0.00000015", + "completion": "0.0000005", "request": "0", "image": "0", "web_search": "0", @@ -365,7 +893,6 @@ "include_reasoning", "logit_bias", "max_tokens", - "min_p", "presence_penalty", "reasoning", "repetition_penalty", @@ -381,7 +908,8 @@ "temperature": 0.6, "top_p": 0.95, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "xiaomi/mimo-v2-flash:free", @@ -389,7 +917,7 @@ "hugging_face_id": "XiaomiMiMo/MiMo-V2-Flash", "name": "Xiaomi: MiMo-V2-Flash (free)", "created": 1765731308, - "description": "MiMo-V2-Flash is an open-source foundation language model developed by Xiaomi. It is a Mixture-of-Experts model with 309B total parameters and 15B active parameters, adopting hybrid attention architecture. MiMo-V2-Flash supports a hybrid-thinking toggle and a 256K context window, and excels at reasoning, coding, and agent scenarios. On SWE-bench Verified and SWE-bench Multilingual, MiMo-V2-Flash ranks as the top #1 open-source model globally, delivering performance comparable to Claude Sonnet 4.5 while costing only about 3.5% as much.\n\nNote: when integrating with agentic tools such as Claude Code, Cline, or Roo Code, **turn off reasoning mode** for the best and fastest performance—this model is deeply optimized for this scenario.\n\nUsers can control the reasoning behaviour with the `reasoning` `enabled` boolean. [Learn more in our docs](https://openrouter.ai/docs/use-cases/reasoning-tokens#enable-reasoning-with-default-config).", + "description": "MiMo-V2-Flash is an open-source foundation language model developed by Xiaomi. It is a Mixture-of-Experts model with 309B total parameters and 15B active parameters, adopting hybrid attention architecture. MiMo-V2-Flash supports a hybrid-thinking toggle and a 256K context window, and excels at reasoning, coding, and agent scenarios. On SWE-bench Verified and SWE-bench Multilingual, MiMo-V2-Flash ranks as the top #1 open-source model globally, delivering performance comparable to Claude Sonnet 4.5 while costing only about 3.5% as much.\n\nUsers can control the reasoning behaviour with the `reasoning` `enabled` boolean. [Learn more in our docs](https://openrouter.ai/docs/use-cases/reasoning-tokens#enable-reasoning-with-default-config).", "context_length": 262144, "architecture": { "modality": "text->text", @@ -433,7 +961,65 @@ "temperature": null, "top_p": 0.95, "frequency_penalty": null - } + }, + "expiration_date": "2026-01-26" + }, + { + "id": "xiaomi/mimo-v2-flash", + "canonical_slug": "xiaomi/mimo-v2-flash-20251210", + "hugging_face_id": "XiaomiMiMo/MiMo-V2-Flash", + "name": "Xiaomi: MiMo-V2-Flash", + "created": 1765731308, + "description": "MiMo-V2-Flash is an open-source foundation language model developed by Xiaomi. It is a Mixture-of-Experts model with 309B total parameters and 15B active parameters, adopting hybrid attention architecture. MiMo-V2-Flash supports a hybrid-thinking toggle and a 256K context window, and excels at reasoning, coding, and agent scenarios. On SWE-bench Verified and SWE-bench Multilingual, MiMo-V2-Flash ranks as the top #1 open-source model globally, delivering performance comparable to Claude Sonnet 4.5 while costing only about 3.5% as much.\n\nUsers can control the reasoning behaviour with the `reasoning` `enabled` boolean. [Learn more in our docs](https://openrouter.ai/docs/use-cases/reasoning-tokens#enable-reasoning-with-default-config).", + "context_length": 262144, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Other", + "instruct_type": null + }, + "pricing": { + "prompt": "0.00000009", + "completion": "0.00000029", + "request": "0", + "image": "0", + "web_search": "0", + "internal_reasoning": "0" + }, + "top_provider": { + "context_length": 262144, + "max_completion_tokens": null, + "is_moderated": false + }, + "per_request_limits": null, + "supported_parameters": [ + "frequency_penalty", + "include_reasoning", + "max_tokens", + "presence_penalty", + "reasoning", + "repetition_penalty", + "response_format", + "seed", + "stop", + "structured_outputs", + "temperature", + "tool_choice", + "tools", + "top_k", + "top_p" + ], + "default_parameters": { + "temperature": null, + "top_p": 0.95, + "frequency_penalty": null + }, + "expiration_date": null }, { "id": "nvidia/nemotron-3-nano-30b-a3b:free", @@ -482,7 +1068,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "nvidia/nemotron-3-nano-30b-a3b", @@ -539,7 +1126,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "openai/gpt-5.2-chat", @@ -550,7 +1138,7 @@ "description": "GPT-5.2 Chat (AKA Instant) is the fast, lightweight member of the 5.2 family, optimized for low-latency chat while retaining strong general intelligence. It uses adaptive reasoning to selectively “think” on harder queries, improving accuracy on math, coding, and multi-step tasks without slowing down typical conversations. The model is warmer and more conversational by default, with better instruction following and more stable short-form reasoning. GPT-5.2 Chat is designed for high-throughput, interactive workloads where responsiveness and consistency matter more than deep deliberation.", "context_length": 128000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "file", "image", @@ -565,10 +1153,7 @@ "pricing": { "prompt": "0.00000175", "completion": "0.000014", - "request": "0", - "image": "0", "web_search": "0.01", - "internal_reasoning": "0", "input_cache_read": "0.000000175" }, "top_provider": { @@ -589,7 +1174,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "openai/gpt-5.2-pro", @@ -600,7 +1186,7 @@ "description": "GPT-5.2 Pro is OpenAI’s most advanced model, offering major improvements in agentic coding and long context performance over GPT-5 Pro. It is optimized for complex tasks that require step-by-step reasoning, instruction following, and accuracy in high-stakes use cases. It supports test-time routing features and advanced prompt understanding, including user-specified intent like \"think hard about this.\" Improvements include reductions in hallucination, sycophancy, and better performance in coding, writing, and health-related tasks.", "context_length": 400000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "image", "text", @@ -615,10 +1201,7 @@ "pricing": { "prompt": "0.000021", "completion": "0.000168", - "request": "0", - "image": "0", - "web_search": "0.01", - "internal_reasoning": "0" + "web_search": "0.01" }, "top_provider": { "context_length": 400000, @@ -640,7 +1223,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "openai/gpt-5.2", @@ -651,7 +1235,7 @@ "description": "GPT-5.2 is the latest frontier-grade model in the GPT-5 series, offering stronger agentic and long context perfomance compared to GPT-5.1. It uses adaptive reasoning to allocate computation dynamically, responding quickly to simple queries while spending more depth on complex tasks.\n\nBuilt for broad task coverage, GPT-5.2 delivers consistent gains across math, coding, sciende, and tool calling workloads, with more coherent long-form answers and improved tool-use reliability.", "context_length": 400000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "file", "image", @@ -666,10 +1250,7 @@ "pricing": { "prompt": "0.00000175", "completion": "0.000014", - "request": "0", - "image": "0", "web_search": "0.01", - "internal_reasoning": "0", "input_cache_read": "0.000000175" }, "top_provider": { @@ -692,7 +1273,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "mistralai/devstral-2512:free", @@ -715,11 +1297,7 @@ }, "pricing": { "prompt": "0", - "completion": "0", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0" }, "top_provider": { "context_length": 262144, @@ -744,7 +1322,8 @@ "temperature": 0.3, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": "2026-01-27" }, { "id": "mistralai/devstral-2512", @@ -798,7 +1377,8 @@ "temperature": 0.3, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "relace/relace-search", @@ -821,12 +1401,7 @@ }, "pricing": { "prompt": "0.000001", - "completion": "0.000003", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0", - "input_cache_read": "0" + "completion": "0.000003" }, "top_provider": { "context_length": 256000, @@ -847,7 +1422,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "z-ai/glm-4.6v", @@ -858,7 +1434,7 @@ "description": "GLM-4.6V is a large multimodal model designed for high-fidelity visual understanding and long-context reasoning across images, documents, and mixed media. It supports up to 128K tokens, processes complex page layouts and charts directly as visual inputs, and integrates native multimodal function calling to connect perception with downstream tool execution. The model also enables interleaved image-text generation and UI reconstruction workflows, including screenshot-to-HTML synthesis and iterative visual editing.", "context_length": 131072, "architecture": { - "modality": "text+image->text", + "modality": "text+image+video->text", "input_modalities": [ "image", "text", @@ -877,11 +1453,11 @@ "image": "0", "web_search": "0", "internal_reasoning": "0", - "input_cache_read": "0.00000005" + "input_cache_read": "0" }, "top_provider": { "context_length": 131072, - "max_completion_tokens": 24000, + "max_completion_tokens": 131072, "is_moderated": false }, "per_request_limits": null, @@ -908,13 +1484,14 @@ "temperature": 0.8, "top_p": 0.6, "frequency_penalty": null - } + }, + "expiration_date": null }, { - "id": "nex-agi/deepseek-v3.1-nex-n1:free", + "id": "nex-agi/deepseek-v3.1-nex-n1", "canonical_slug": "nex-agi/deepseek-v3.1-nex-n1", "hugging_face_id": "nex-agi/DeepSeek-V3.1-Nex-N1", - "name": "Nex AGI: DeepSeek V3.1 Nex N1 (free)", + "name": "Nex AGI: DeepSeek V3.1 Nex N1", "created": 1765204393, "description": "DeepSeek V3.1 Nex-N1 is the flagship release of the Nex-N1 series — a post-trained model designed to highlight agent autonomy, tool use, and real-world productivity. \n\nNex-N1 demonstrates competitive performance across all evaluation scenarios, showing particularly strong results in practical coding and HTML generation tasks.", "context_length": 131072, @@ -930,8 +1507,8 @@ "instruct_type": null }, "pricing": { - "prompt": "0", - "completion": "0", + "prompt": "0.00000027", + "completion": "0.000001", "request": "0", "image": "0", "web_search": "0", @@ -959,7 +1536,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "essentialai/rnj-1-instruct", @@ -1012,7 +1590,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "openrouter/bodybuilder", @@ -1048,7 +1627,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "openai/gpt-5.1-codex-max", @@ -1073,10 +1653,7 @@ "pricing": { "prompt": "0.00000125", "completion": "0.00001", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0", + "web_search": "0.01", "input_cache_read": "0.000000125" }, "top_provider": { @@ -1099,7 +1676,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "amazon/nova-2-lite-v1", @@ -1110,7 +1688,7 @@ "description": "Nova 2 Lite is a fast, cost-effective reasoning model for everyday workloads that can process text, images, and videos to generate text. \n\nNova 2 Lite demonstrates standout capabilities in processing documents, extracting information from videos, generating code, providing accurate grounded answers, and automating multi-step agentic workflows.", "context_length": 1000000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file+video->text", "input_modalities": [ "text", "image", @@ -1152,7 +1730,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "mistralai/ministral-14b-2512", @@ -1176,11 +1755,7 @@ }, "pricing": { "prompt": "0.0000002", - "completion": "0.0000002", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.0000002" }, "top_provider": { "context_length": 262144, @@ -1209,7 +1784,8 @@ "temperature": 0.3, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "mistralai/ministral-8b-2512", @@ -1233,11 +1809,7 @@ }, "pricing": { "prompt": "0.00000015", - "completion": "0.00000015", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.00000015" }, "top_provider": { "context_length": 262144, @@ -1262,7 +1834,8 @@ "temperature": 0.3, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "mistralai/ministral-3b-2512", @@ -1286,11 +1859,7 @@ }, "pricing": { "prompt": "0.0000001", - "completion": "0.0000001", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.0000001" }, "top_provider": { "context_length": 131072, @@ -1315,7 +1884,8 @@ "temperature": 0.3, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "mistralai/mistral-large-2512", @@ -1339,11 +1909,7 @@ }, "pricing": { "prompt": "0.0000005", - "completion": "0.0000015", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.0000015" }, "top_provider": { "context_length": 262144, @@ -1368,7 +1934,8 @@ "temperature": 0.0645, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "arcee-ai/trinity-mini:free", @@ -1419,7 +1986,8 @@ "temperature": 0.15, "top_p": 0.75, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "arcee-ai/trinity-mini", @@ -1477,7 +2045,8 @@ "temperature": 0.15, "top_p": 0.75, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "deepseek/deepseek-v3.2-speciale", @@ -1517,7 +2086,6 @@ "include_reasoning", "logit_bias", "max_tokens", - "min_p", "presence_penalty", "reasoning", "repetition_penalty", @@ -1533,7 +2101,8 @@ "temperature": 1, "top_p": 0.95, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "deepseek/deepseek-v3.2", @@ -1593,7 +2162,8 @@ "temperature": 1, "top_p": 0.95, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "prime-intellect/intellect-3", @@ -1633,7 +2203,6 @@ "include_reasoning", "logit_bias", "max_tokens", - "min_p", "presence_penalty", "reasoning", "repetition_penalty", @@ -1651,7 +2220,8 @@ "temperature": 0.6, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "tngtech/tng-r1t-chimera:free", @@ -1682,7 +2252,7 @@ }, "top_provider": { "context_length": 163840, - "max_completion_tokens": 163840, + "max_completion_tokens": 65536, "is_moderated": false }, "per_request_limits": null, @@ -1707,7 +2277,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "tngtech/tng-r1t-chimera", @@ -1763,7 +2334,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "anthropic/claude-opus-4.5", @@ -1774,7 +2346,7 @@ "description": "Claude Opus 4.5 is Anthropic’s frontier reasoning model optimized for complex software engineering, agentic workflows, and long-horizon computer use. It offers strong multimodal capabilities, competitive performance across real-world coding and reasoning benchmarks, and improved robustness to prompt injection. The model is designed to operate efficiently across varied effort levels, enabling developers to trade off speed, depth, and token usage depending on task requirements. It comes with a new parameter to control token efficiency, which can be accessed using the OpenRouter Verbosity parameter with low, medium, or high.\n\nOpus 4.5 supports advanced tool use, extended context management, and coordinated multi-agent setups, making it well-suited for autonomous research, debugging, multi-step planning, and spreadsheet/browser manipulation. It delivers substantial gains in structured reasoning, execution reliability, and alignment compared to prior Opus generations, while reducing token overhead and improving performance on long-running tasks.", "context_length": 200000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "file", "image", @@ -1789,16 +2361,13 @@ "pricing": { "prompt": "0.000005", "completion": "0.000025", - "request": "0", - "image": "0", "web_search": "0.01", - "internal_reasoning": "0", "input_cache_read": "0.0000005", "input_cache_write": "0.00000625" }, "top_provider": { "context_length": 200000, - "max_completion_tokens": 32000, + "max_completion_tokens": 64000, "is_moderated": true }, "per_request_limits": null, @@ -1819,13 +2388,14 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { - "id": "allenai/olmo-3-32b-think:free", + "id": "allenai/olmo-3-32b-think", "canonical_slug": "allenai/olmo-3-32b-think-20251121", "hugging_face_id": "allenai/Olmo-3-32B-Think", - "name": "AllenAI: Olmo 3 32B Think (free)", + "name": "AllenAI: Olmo 3 32B Think", "created": 1763758276, "description": "Olmo 3 32B Think is a large-scale, 32-billion-parameter model purpose-built for deep reasoning, complex logic chains and advanced instruction-following scenarios. Its capacity enables strong performance on demanding evaluation tasks and highly nuanced conversational reasoning. Developed by Ai2 under the Apache 2.0 license, Olmo 3 32B Think embodies the Olmo initiative’s commitment to openness, offering full transparency across weights, code and training methodology.", "context_length": 65536, @@ -1841,8 +2411,8 @@ "instruct_type": null }, "pricing": { - "prompt": "0", - "completion": "0", + "prompt": "0.00000015", + "completion": "0.0000005", "request": "0", "image": "0", "web_search": "0", @@ -1859,7 +2429,6 @@ "include_reasoning", "logit_bias", "max_tokens", - "min_p", "presence_penalty", "reasoning", "repetition_penalty", @@ -1875,7 +2444,8 @@ "temperature": 0.6, "top_p": 0.95, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "allenai/olmo-3-7b-instruct", @@ -1914,7 +2484,6 @@ "frequency_penalty", "logit_bias", "max_tokens", - "min_p", "presence_penalty", "repetition_penalty", "response_format", @@ -1922,8 +2491,6 @@ "stop", "structured_outputs", "temperature", - "tool_choice", - "tools", "top_k", "top_p" ], @@ -1931,7 +2498,8 @@ "temperature": 0.6, "top_p": 0.95, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "allenai/olmo-3-7b-think", @@ -1971,7 +2539,6 @@ "include_reasoning", "logit_bias", "max_tokens", - "min_p", "presence_penalty", "reasoning", "repetition_penalty", @@ -1987,7 +2554,8 @@ "temperature": 0.6, "top_p": 0.95, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "google/gemini-3-pro-image-preview", @@ -2013,10 +2581,11 @@ "pricing": { "prompt": "0.000002", "completion": "0.000012", - "request": "0", - "image": "0.067", - "web_search": "0", - "internal_reasoning": "0" + "image": "0.000002", + "audio": "0.000002", + "internal_reasoning": "0.000012", + "input_cache_read": "0.0000002", + "input_cache_write": "0.000000375" }, "top_provider": { "context_length": 65536, @@ -2030,6 +2599,7 @@ "reasoning", "response_format", "seed", + "stop", "structured_outputs", "temperature", "top_p" @@ -2038,7 +2608,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "x-ai/grok-4.1-fast", @@ -2093,7 +2664,8 @@ "temperature": 0.7, "top_p": 0.95, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "google/gemini-3-pro-preview", @@ -2104,7 +2676,7 @@ "description": "Gemini 3 Pro is Google’s flagship frontier model for high-precision multimodal reasoning, combining strong performance across text, image, video, audio, and code with a 1M-token context window. Reasoning Details must be preserved when using multi-turn tool calling, see our docs here: https://openrouter.ai/docs/use-cases/reasoning-tokens#preserving-reasoning-blocks. It delivers state-of-the-art benchmark results in general reasoning, STEM problem solving, factual QA, and multimodal understanding, including leading scores on LMArena, GPQA Diamond, MathArena Apex, MMMU-Pro, and Video-MMMU. Interactions emphasize depth and interpretability: the model is designed to infer intent with minimal prompting and produce direct, insight-focused responses.\n\nBuilt for advanced development and agentic workflows, Gemini 3 Pro provides robust tool-calling, long-horizon planning stability, and strong zero-shot generation for complex UI, visualization, and coding tasks. It excels at agentic coding (SWE-Bench Verified, Terminal-Bench 2.0), multimodal analysis, and structured long-form tasks such as research synthesis, planning, and interactive learning experiences. Suitable applications include autonomous agents, coding assistants, multimodal analytics, scientific reasoning, and high-context information processing.", "context_length": 1048576, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file+audio+video->text", "input_modalities": [ "text", "image", @@ -2121,12 +2693,11 @@ "pricing": { "prompt": "0.000002", "completion": "0.000012", - "request": "0", - "image": "0.008256", - "web_search": "0", - "internal_reasoning": "0", + "image": "0.000002", + "audio": "0.000002", + "internal_reasoning": "0.000012", "input_cache_read": "0.0000002", - "input_cache_write": "0.000002375" + "input_cache_write": "0.000000375" }, "top_provider": { "context_length": 1048576, @@ -2151,7 +2722,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "deepcogito/cogito-v2.1-671b", @@ -2206,7 +2778,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "openai/gpt-5.1", @@ -2217,7 +2790,7 @@ "description": "GPT-5.1 is the latest frontier-grade model in the GPT-5 series, offering stronger general-purpose reasoning, improved instruction adherence, and a more natural conversational style compared to GPT-5. It uses adaptive reasoning to allocate computation dynamically, responding quickly to simple queries while spending more depth on complex tasks. The model produces clearer, more grounded explanations with reduced jargon, making it easier to follow even on technical or multi-step problems.\n\nBuilt for broad task coverage, GPT-5.1 delivers consistent gains across math, coding, and structured analysis workloads, with more coherent long-form answers and improved tool-use reliability. It also features refined conversational alignment, enabling warmer, more intuitive responses without compromising precision. GPT-5.1 serves as the primary full-capability successor to GPT-5", "context_length": 400000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "image", "text", @@ -2232,10 +2805,7 @@ "pricing": { "prompt": "0.00000125", "completion": "0.00001", - "request": "0", - "image": "0", "web_search": "0.01", - "internal_reasoning": "0", "input_cache_read": "0.000000125" }, "top_provider": { @@ -2258,7 +2828,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "openai/gpt-5.1-chat", @@ -2269,7 +2840,7 @@ "description": "GPT-5.1 Chat (AKA Instant is the fast, lightweight member of the 5.1 family, optimized for low-latency chat while retaining strong general intelligence. It uses adaptive reasoning to selectively “think” on harder queries, improving accuracy on math, coding, and multi-step tasks without slowing down typical conversations. The model is warmer and more conversational by default, with better instruction following and more stable short-form reasoning. GPT-5.1 Chat is designed for high-throughput, interactive workloads where responsiveness and consistency matter more than deep deliberation.\n", "context_length": 128000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "file", "image", @@ -2284,10 +2855,7 @@ "pricing": { "prompt": "0.00000125", "completion": "0.00001", - "request": "0", - "image": "0", "web_search": "0.01", - "internal_reasoning": "0", "input_cache_read": "0.000000125" }, "top_provider": { @@ -2308,7 +2876,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "openai/gpt-5.1-codex", @@ -2333,10 +2902,6 @@ "pricing": { "prompt": "0.00000125", "completion": "0.00001", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0", "input_cache_read": "0.000000125" }, "top_provider": { @@ -2359,7 +2924,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "openai/gpt-5.1-codex-mini", @@ -2384,10 +2950,6 @@ "pricing": { "prompt": "0.00000025", "completion": "0.000002", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0", "input_cache_read": "0.000000025" }, "top_provider": { @@ -2410,13 +2972,14 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { - "id": "kwaipilot/kat-coder-pro:free", + "id": "kwaipilot/kat-coder-pro", "canonical_slug": "kwaipilot/kat-coder-pro-v1", "hugging_face_id": "", - "name": "Kwaipilot: KAT-Coder-Pro V1 (free)", + "name": "Kwaipilot: KAT-Coder-Pro V1", "created": 1762745912, "description": "KAT-Coder-Pro V1 is KwaiKAT's most advanced agentic coding model in the KAT-Coder series. Designed specifically for agentic coding tasks, it excels in real-world software engineering scenarios, achieving 73.4% solve rate on the SWE-Bench Verified benchmark. \n\nThe model has been optimized for tool-use capability, multi-turn interaction, instruction following, generalization, and comprehensive capabilities through a multi-stage training process, including mid-training, supervised fine-tuning (SFT), reinforcement fine-tuning (RFT), and scalable agentic RL.", "context_length": 256000, @@ -2432,16 +2995,17 @@ "instruct_type": null }, "pricing": { - "prompt": "0", - "completion": "0", + "prompt": "0.000000207", + "completion": "0.000000828", "request": "0", "image": "0", "web_search": "0", - "internal_reasoning": "0" + "internal_reasoning": "0", + "input_cache_read": "0.0000000414" }, "top_provider": { "context_length": 256000, - "max_completion_tokens": 32768, + "max_completion_tokens": 128000, "is_moderated": false }, "per_request_limits": null, @@ -2464,7 +3028,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "moonshotai/kimi-k2-thinking", @@ -2524,7 +3089,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "amazon/nova-premier-v1", @@ -2573,7 +3139,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "perplexity/sonar-pro-search", @@ -2625,7 +3192,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "mistralai/voxtral-small-24b-2507", @@ -2636,7 +3204,7 @@ "description": "Voxtral Small is an enhancement of Mistral Small 3, incorporating state-of-the-art audio input capabilities while retaining best-in-class text performance. It excels at speech transcription, translation and audio understanding. Input audio is priced at $100 per million seconds.", "context_length": 32000, "architecture": { - "modality": "text->text", + "modality": "text+audio->text", "input_modalities": [ "text", "audio" @@ -2650,11 +3218,7 @@ "pricing": { "prompt": "0.0000001", "completion": "0.0000003", - "request": "0", - "image": "0", - "audio": "0.0001", - "web_search": "0", - "internal_reasoning": "0" + "audio": "0.0001" }, "top_provider": { "context_length": 32000, @@ -2679,7 +3243,8 @@ "temperature": 0.2, "top_p": 0.95, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "openai/gpt-oss-safeguard-20b", @@ -2731,7 +3296,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "nvidia/nemotron-nano-12b-v2-vl:free", @@ -2742,7 +3308,7 @@ "description": "NVIDIA Nemotron Nano 2 VL is a 12-billion-parameter open multimodal reasoning model designed for video understanding and document intelligence. It introduces a hybrid Transformer-Mamba architecture, combining transformer-level accuracy with Mamba’s memory-efficient sequence modeling for significantly higher throughput and lower latency.\n\nThe model supports inputs of text and multi-image documents, producing natural-language outputs. It is trained on high-quality NVIDIA-curated synthetic datasets optimized for optical-character recognition, chart reasoning, and multimodal comprehension.\n\nNemotron Nano 2 VL achieves leading results on OCRBench v2 and scores ≈ 74 average across MMMU, MathVista, AI2D, OCRBench, OCR-Reasoning, ChartQA, DocVQA, and Video-MME—surpassing prior open VL baselines. With Efficient Video Sampling (EVS), it handles long-form videos while reducing inference cost.\n\nOpen-weights, training data, and fine-tuning recipes are released under a permissive NVIDIA open license, with deployment supported across NeMo, NIM, and major inference runtimes.", "context_length": 128000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+video->text", "input_modalities": [ "image", "text", @@ -2782,7 +3348,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "nvidia/nemotron-nano-12b-v2-vl", @@ -2793,7 +3360,7 @@ "description": "NVIDIA Nemotron Nano 2 VL is a 12-billion-parameter open multimodal reasoning model designed for video understanding and document intelligence. It introduces a hybrid Transformer-Mamba architecture, combining transformer-level accuracy with Mamba’s memory-efficient sequence modeling for significantly higher throughput and lower latency.\n\nThe model supports inputs of text and multi-image documents, producing natural-language outputs. It is trained on high-quality NVIDIA-curated synthetic datasets optimized for optical-character recognition, chart reasoning, and multimodal comprehension.\n\nNemotron Nano 2 VL achieves leading results on OCRBench v2 and scores ≈ 74 average across MMMU, MathVista, AI2D, OCRBench, OCR-Reasoning, ChartQA, DocVQA, and Video-MME—surpassing prior open VL baselines. With Efficient Video Sampling (EVS), it handles long-form videos while reducing inference cost.\n\nOpen-weights, training data, and fine-tuning recipes are released under a permissive NVIDIA open license, with deployment supported across NeMo, NIM, and major inference runtimes.", "context_length": 131072, "architecture": { - "modality": "text+image->text", + "modality": "text+image+video->text", "input_modalities": [ "image", "text", @@ -2838,7 +3405,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "minimax/minimax-m2", @@ -2896,7 +3464,8 @@ "temperature": 1, "top_p": 0.95, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "qwen/qwen3-vl-32b-instruct", @@ -2950,15 +3519,16 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "liquid/lfm2-8b-a1b", "canonical_slug": "liquid/lfm2-8b-a1b", "hugging_face_id": "LiquidAI/LFM2-8B-A1B", - "name": "LiquidAI/LFM2-8B-A1B", + "name": "LiquidAI: LFM2-8B-A1B", "created": 1760970984, - "description": "Model created via inbox interface", + "description": "LFM2-8B-A1B is an efficient on-device Mixture-of-Experts (MoE) model from Liquid AI’s LFM2 family, built for fast, high-quality inference on edge hardware. It uses 8.3B total parameters with only ~1.5B active per token, delivering strong performance while keeping compute and memory usage low—making it ideal for phones, tablets, and laptops.", "context_length": 32768, "architecture": { "modality": "text->text", @@ -2972,59 +3542,8 @@ "instruct_type": null }, "pricing": { - "prompt": "0.00000005", - "completion": "0.0000001", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 32768, - "max_completion_tokens": null, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "frequency_penalty", - "max_tokens", - "min_p", - "presence_penalty", - "repetition_penalty", - "seed", - "stop", - "temperature", - "top_k", - "top_p" - ], - "default_parameters": {} - }, - { - "id": "liquid/lfm-2.2-6b", - "canonical_slug": "liquid/lfm-2.2-6b", - "hugging_face_id": "LiquidAI/LFM2-2.6B", - "name": "LiquidAI/LFM2-2.6B", - "created": 1760970889, - "description": "LFM2 is a new generation of hybrid models developed by Liquid AI, specifically designed for edge AI and on-device deployment. It sets a new standard in terms of quality, speed, and memory efficiency.", - "context_length": 32768, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Other", - "instruct_type": null - }, - "pricing": { - "prompt": "0.00000005", - "completion": "0.0000001", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "prompt": "0.00000001", + "completion": "0.00000002" }, "top_provider": { "context_length": 32768, @@ -3048,7 +3567,56 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null + }, + { + "id": "liquid/lfm-2.2-6b", + "canonical_slug": "liquid/lfm-2.2-6b", + "hugging_face_id": "LiquidAI/LFM2-2.6B", + "name": "LiquidAI: LFM2-2.6B", + "created": 1760970889, + "description": "LFM2 is a new generation of hybrid models developed by Liquid AI, specifically designed for edge AI and on-device deployment. It sets a new standard in terms of quality, speed, and memory efficiency.", + "context_length": 32768, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Other", + "instruct_type": null + }, + "pricing": { + "prompt": "0.00000001", + "completion": "0.00000002" + }, + "top_provider": { + "context_length": 32768, + "max_completion_tokens": null, + "is_moderated": false + }, + "per_request_limits": null, + "supported_parameters": [ + "frequency_penalty", + "max_tokens", + "min_p", + "presence_penalty", + "repetition_penalty", + "seed", + "stop", + "temperature", + "top_k", + "top_p" + ], + "default_parameters": { + "temperature": null, + "top_p": null, + "frequency_penalty": null + }, + "expiration_date": null }, { "id": "ibm-granite/granite-4.0-h-micro", @@ -3097,7 +3665,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "deepcogito/cogito-v2-preview-llama-405b", @@ -3154,7 +3723,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": "2026-02-04" }, { "id": "openai/gpt-5-image-mini", @@ -3165,7 +3735,7 @@ "description": "GPT-5 Image Mini combines OpenAI's advanced language capabilities, powered by [GPT-5 Mini](https://openrouter.ai/openai/gpt-5-mini), with GPT Image 1 Mini for efficient image generation. This natively multimodal model features superior instruction following, text rendering, and detailed image editing with reduced latency and cost. It excels at high-quality visual creation while maintaining strong text understanding, making it ideal for applications that require both efficient image generation and text processing at scale.", "context_length": 400000, "architecture": { - "modality": "text+image->text+image", + "modality": "text+image+file->text+image", "input_modalities": [ "file", "image", @@ -3181,10 +3751,7 @@ "pricing": { "prompt": "0.0000025", "completion": "0.000002", - "request": "0", - "image": "0.0000025", "web_search": "0.01", - "internal_reasoning": "0", "input_cache_read": "0.00000025" }, "top_provider": { @@ -3215,7 +3782,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "anthropic/claude-haiku-4.5", @@ -3240,10 +3808,7 @@ "pricing": { "prompt": "0.000001", "completion": "0.000005", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0", + "web_search": "0.01", "input_cache_read": "0.0000001", "input_cache_write": "0.00000125" }, @@ -3268,7 +3833,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "qwen/qwen3-vl-8b-thinking", @@ -3320,7 +3886,8 @@ "default_parameters": { "temperature": 1, "top_p": 0.95 - } + }, + "expiration_date": null }, { "id": "qwen/qwen3-vl-8b-instruct", @@ -3343,8 +3910,8 @@ "instruct_type": null }, "pricing": { - "prompt": "0.000000064", - "completion": "0.0000004", + "prompt": "0.00000008", + "completion": "0.0000005", "request": "0", "image": "0", "web_search": "0", @@ -3378,7 +3945,8 @@ "temperature": 0.7, "top_p": 0.8, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "openai/gpt-5-image", @@ -3389,7 +3957,7 @@ "description": "[GPT-5](https://openrouter.ai/openai/gpt-5) Image combines OpenAI's GPT-5 model with state-of-the-art image generation capabilities. It offers major improvements in reasoning, code quality, and user experience while incorporating GPT Image 1's superior instruction following, text rendering, and detailed image editing.", "context_length": 400000, "architecture": { - "modality": "text+image->text+image", + "modality": "text+image+file->text+image", "input_modalities": [ "image", "text", @@ -3405,10 +3973,7 @@ "pricing": { "prompt": "0.00001", "completion": "0.00001", - "request": "0", - "image": "0.00001", "web_search": "0.01", - "internal_reasoning": "0", "input_cache_read": "0.00000125" }, "top_provider": { @@ -3439,7 +4004,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "openai/o3-deep-research", @@ -3450,7 +4016,7 @@ "description": "o3-deep-research is OpenAI's advanced model for deep research, designed to tackle complex, multi-step research tasks.\n\nNote: This model always uses the 'web_search' tool which adds additional cost.", "context_length": 200000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "image", "text", @@ -3465,10 +4031,7 @@ "pricing": { "prompt": "0.00001", "completion": "0.00004", - "request": "0", - "image": "0.00765", "web_search": "0.01", - "internal_reasoning": "0", "input_cache_read": "0.0000025" }, "top_provider": { @@ -3499,7 +4062,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "openai/o4-mini-deep-research", @@ -3510,7 +4074,7 @@ "description": "o4-mini-deep-research is OpenAI's faster, more affordable deep research model—ideal for tackling complex, multi-step research tasks.\n\nNote: This model always uses the 'web_search' tool which adds additional cost.", "context_length": 200000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "file", "image", @@ -3525,10 +4089,7 @@ "pricing": { "prompt": "0.000002", "completion": "0.000008", - "request": "0", - "image": "0.00153", "web_search": "0.01", - "internal_reasoning": "0", "input_cache_read": "0.0000005" }, "top_provider": { @@ -3559,7 +4120,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "nvidia/llama-3.3-nemotron-super-49b-v1.5", @@ -3611,7 +4173,8 @@ "top_k", "top_p" ], - "default_parameters": null + "default_parameters": null, + "expiration_date": null }, { "id": "baidu/ernie-4.5-21b-a3b-thinking", @@ -3633,8 +4196,8 @@ "instruct_type": null }, "pricing": { - "prompt": "0.000000056", - "completion": "0.000000224", + "prompt": "0.00000007", + "completion": "0.00000028", "request": "0", "image": "0", "web_search": "0", @@ -3663,7 +4226,8 @@ "temperature": 0.6, "top_p": 0.95, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "google/gemini-2.5-flash-image", @@ -3689,10 +4253,11 @@ "pricing": { "prompt": "0.0000003", "completion": "0.0000025", - "request": "0", - "image": "0.001238", - "web_search": "0", - "internal_reasoning": "0" + "image": "0.0000003", + "audio": "0.000001", + "internal_reasoning": "0.0000025", + "input_cache_read": "0.00000003", + "input_cache_write": "0.00000008333333333333334" }, "top_provider": { "context_length": 32768, @@ -3712,7 +4277,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "qwen/qwen3-vl-30b-a3b-thinking", @@ -3735,8 +4301,8 @@ "instruct_type": null }, "pricing": { - "prompt": "0.00000016", - "completion": "0.0000008", + "prompt": "0.0000002", + "completion": "0.000001", "request": "0", "image": "0", "web_search": "0", @@ -3769,7 +4335,8 @@ "default_parameters": { "temperature": 0.8, "top_p": 0.95 - } + }, + "expiration_date": null }, { "id": "qwen/qwen3-vl-30b-a3b-instruct", @@ -3828,7 +4395,8 @@ "temperature": 0.7, "top_p": 0.8, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "openai/gpt-5-pro", @@ -3839,7 +4407,7 @@ "description": "GPT-5 Pro is OpenAI’s most advanced model, offering major improvements in reasoning, code quality, and user experience. It is optimized for complex tasks that require step-by-step reasoning, instruction following, and accuracy in high-stakes use cases. It supports test-time routing features and advanced prompt understanding, including user-specified intent like \"think hard about this.\" Improvements include reductions in hallucination, sycophancy, and better performance in coding, writing, and health-related tasks.", "context_length": 400000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "image", "text", @@ -3854,10 +4422,7 @@ "pricing": { "prompt": "0.000015", "completion": "0.00012", - "request": "0", - "image": "0", - "web_search": "0.01", - "internal_reasoning": "0" + "web_search": "0.01" }, "top_provider": { "context_length": 400000, @@ -3879,7 +4444,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "z-ai/glm-4.6", @@ -3940,7 +4506,8 @@ "temperature": 0.6, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "z-ai/glm-4.6:exacto", @@ -3996,7 +4563,8 @@ "temperature": 0.6, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "anthropic/claude-sonnet-4.5", @@ -4007,7 +4575,7 @@ "description": "Claude Sonnet 4.5 is Anthropic’s most advanced Sonnet model to date, optimized for real-world agents and coding workflows. It delivers state-of-the-art performance on coding benchmarks such as SWE-bench Verified, with improvements across system design, code security, and specification adherence. The model is designed for extended autonomous operation, maintaining task continuity across sessions and providing fact-based progress tracking.\n\nSonnet 4.5 also introduces stronger agentic capabilities, including improved tool orchestration, speculative parallel execution, and more efficient context and memory management. With enhanced context tracking and awareness of token usage across tool calls, it is particularly well-suited for multi-context and long-running workflows. Use cases span software engineering, cybersecurity, financial analysis, research agents, and other domains requiring sustained reasoning and tool use.", "context_length": 1000000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "text", "image", @@ -4022,17 +4590,14 @@ "pricing": { "prompt": "0.000003", "completion": "0.000015", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0", + "web_search": "0.01", "input_cache_read": "0.0000003", "input_cache_write": "0.00000375" }, "top_provider": { "context_length": 1000000, "max_completion_tokens": 64000, - "is_moderated": false + "is_moderated": true }, "per_request_limits": null, "supported_parameters": [ @@ -4052,7 +4617,8 @@ "temperature": 1, "top_p": 1, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "deepseek/deepseek-v3.2-exp", @@ -4091,7 +4657,6 @@ "frequency_penalty", "include_reasoning", "max_tokens", - "min_p", "presence_penalty", "reasoning", "repetition_penalty", @@ -4109,7 +4674,8 @@ "temperature": 0.6, "top_p": 0.95, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "thedrummer/cydonia-24b-v4.1", @@ -4148,7 +4714,6 @@ "frequency_penalty", "logit_bias", "max_tokens", - "min_p", "presence_penalty", "repetition_penalty", "response_format", @@ -4163,7 +4728,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "relace/relace-apply-3", @@ -4207,7 +4773,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "google/gemini-2.5-flash-preview-09-2025", @@ -4218,7 +4785,7 @@ "description": "Gemini 2.5 Flash Preview September 2025 Checkpoint is Google's state-of-the-art workhorse model, specifically designed for advanced reasoning, coding, mathematics, and scientific tasks. It includes built-in \"thinking\" capabilities, enabling it to provide responses with greater accuracy and nuanced context handling. \n\nAdditionally, Gemini 2.5 Flash is configurable through the \"max tokens for reasoning\" parameter, as described in the documentation (https://openrouter.ai/docs/use-cases/reasoning-tokens#max-tokens-for-reasoning).", "context_length": 1048576, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file+audio+video->text", "input_modalities": [ "image", "file", @@ -4235,17 +4802,15 @@ "pricing": { "prompt": "0.0000003", "completion": "0.0000025", - "request": "0", - "image": "0.001238", + "image": "0.0000003", "audio": "0.000001", - "web_search": "0", - "internal_reasoning": "0", - "input_cache_read": "0.000000075", - "input_cache_write": "0.0000003833" + "internal_reasoning": "0.0000025", + "input_cache_read": "0.00000003", + "input_cache_write": "0.00000008333333333333334" }, "top_provider": { "context_length": 1048576, - "max_completion_tokens": 65536, + "max_completion_tokens": 65535, "is_moderated": false }, "per_request_limits": null, @@ -4266,7 +4831,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": "2026-02-17" }, { "id": "google/gemini-2.5-flash-lite-preview-09-2025", @@ -4277,7 +4843,7 @@ "description": "Gemini 2.5 Flash-Lite is a lightweight reasoning model in the Gemini 2.5 family, optimized for ultra-low latency and cost efficiency. It offers improved throughput, faster token generation, and better performance across common benchmarks compared to earlier Flash models. By default, \"thinking\" (i.e. multi-pass reasoning) is disabled to prioritize speed, but developers can enable it via the [Reasoning API parameter](https://openrouter.ai/docs/use-cases/reasoning-tokens) to selectively trade off cost for intelligence. ", "context_length": 1048576, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file+audio+video->text", "input_modalities": [ "text", "image", @@ -4294,14 +4860,15 @@ "pricing": { "prompt": "0.0000001", "completion": "0.0000004", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "image": "0.0000001", + "audio": "0.0000003", + "internal_reasoning": "0.0000004", + "input_cache_read": "0.00000001", + "input_cache_write": "0.00000008333333333333334" }, "top_provider": { "context_length": 1048576, - "max_completion_tokens": 65536, + "max_completion_tokens": 65535, "is_moderated": false }, "per_request_limits": null, @@ -4322,7 +4889,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "qwen/qwen3-vl-235b-a22b-thinking", @@ -4345,8 +4913,8 @@ "instruct_type": null }, "pricing": { - "prompt": "0.0000003", - "completion": "0.0000012", + "prompt": "0.00000045", + "completion": "0.0000035", "request": "0", "image": "0", "web_search": "0", @@ -4379,7 +4947,8 @@ "temperature": 0.8, "top_p": 0.95, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "qwen/qwen3-vl-235b-a22b-instruct", @@ -4438,7 +5007,8 @@ "temperature": 0.7, "top_p": 0.8, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "qwen/qwen3-max", @@ -4488,7 +5058,8 @@ "temperature": 1, "top_p": 1, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "qwen/qwen3-coder-plus", @@ -4539,7 +5110,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "openai/gpt-5-codex", @@ -4564,10 +5136,6 @@ "pricing": { "prompt": "0.00000125", "completion": "0.00001", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0", "input_cache_read": "0.000000125" }, "top_provider": { @@ -4590,7 +5158,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "deepseek/deepseek-v3.1-terminus:exacto", @@ -4648,7 +5217,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "deepseek/deepseek-v3.1-terminus", @@ -4706,7 +5276,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "x-ai/grok-4-fast", @@ -4761,63 +5332,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } - }, - { - "id": "alibaba/tongyi-deepresearch-30b-a3b:free", - "canonical_slug": "alibaba/tongyi-deepresearch-30b-a3b", - "hugging_face_id": "Alibaba-NLP/Tongyi-DeepResearch-30B-A3B", - "name": "Tongyi DeepResearch 30B A3B (free)", - "created": 1758210804, - "description": "Tongyi DeepResearch is an agentic large language model developed by Tongyi Lab, with 30 billion total parameters activating only 3 billion per token. It's optimized for long-horizon, deep information-seeking tasks and delivers state-of-the-art performance on benchmarks like Humanity's Last Exam, BrowserComp, BrowserComp-ZH, WebWalkerQA, GAIA, xbench-DeepSearch, and FRAMES. This makes it superior for complex agentic search, reasoning, and multi-step problem-solving compared to prior models.\n\nThe model includes a fully automated synthetic data pipeline for scalable pre-training, fine-tuning, and reinforcement learning. It uses large-scale continual pre-training on diverse agentic data to boost reasoning and stay fresh. It also features end-to-end on-policy RL with a customized Group Relative Policy Optimization, including token-level gradients and negative sample filtering for stable training. The model supports ReAct for core ability checks and an IterResearch-based 'Heavy' mode for max performance through test-time scaling. It's ideal for advanced research agents, tool use, and heavy inference workflows.", - "context_length": 131072, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Other", - "instruct_type": null }, - "pricing": { - "prompt": "0", - "completion": "0", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 131072, - "max_completion_tokens": 131072, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "frequency_penalty", - "include_reasoning", - "max_tokens", - "presence_penalty", - "reasoning", - "repetition_penalty", - "response_format", - "seed", - "stop", - "structured_outputs", - "temperature", - "tool_choice", - "tools", - "top_k", - "top_p" - ], - "default_parameters": { - "temperature": null, - "top_p": null, - "frequency_penalty": null - } + "expiration_date": null }, { "id": "alibaba/tongyi-deepresearch-30b-a3b", @@ -4840,11 +5356,7 @@ }, "pricing": { "prompt": "0.00000009", - "completion": "0.0000004", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.0000004" }, "top_provider": { "context_length": 131072, @@ -4874,7 +5386,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "qwen/qwen3-coder-flash", @@ -4924,7 +5437,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "opengvlab/internvl3-78b", @@ -4973,7 +5487,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "qwen/qwen3-next-80b-a3b-thinking", @@ -4982,7 +5497,7 @@ "name": "Qwen: Qwen3 Next 80B A3B Thinking", "created": 1757612284, "description": "Qwen3-Next-80B-A3B-Thinking is a reasoning-first chat model in the Qwen3-Next line that outputs structured “thinking” traces by default. It’s designed for hard multi-step problems; math proofs, code synthesis/debugging, logic, and agentic planning, and reports strong results across knowledge, reasoning, coding, alignment, and multilingual evaluations. Compared with prior Qwen3 variants, it emphasizes stability under long chains of thought and efficient scaling during inference, and it is tuned to follow complex instructions while reducing repetitive or off-task behavior.\n\nThe model is suitable for agent frameworks and tool use (function calling), retrieval-heavy workflows, and standardized benchmarking where step-by-step solutions are required. It supports long, detailed completions and leverages throughput-oriented techniques (e.g., multi-token prediction) for faster generation. Note that it operates in thinking-only mode.", - "context_length": 131072, + "context_length": 128000, "architecture": { "modality": "text->text", "input_modalities": [ @@ -4995,7 +5510,7 @@ "instruct_type": null }, "pricing": { - "prompt": "0.00000012", + "prompt": "0.00000015", "completion": "0.0000012", "request": "0", "image": "0", @@ -5003,8 +5518,8 @@ "internal_reasoning": "0" }, "top_provider": { - "context_length": 131072, - "max_completion_tokens": 32768, + "context_length": 128000, + "max_completion_tokens": null, "is_moderated": false }, "per_request_limits": null, @@ -5012,7 +5527,6 @@ "frequency_penalty", "include_reasoning", "logit_bias", - "logprobs", "max_tokens", "min_p", "presence_penalty", @@ -5026,14 +5540,63 @@ "tool_choice", "tools", "top_k", - "top_logprobs", "top_p" ], "default_parameters": { "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null + }, + { + "id": "qwen/qwen3-next-80b-a3b-instruct:free", + "canonical_slug": "qwen/qwen3-next-80b-a3b-instruct-2509", + "hugging_face_id": "Qwen/Qwen3-Next-80B-A3B-Instruct", + "name": "Qwen: Qwen3 Next 80B A3B Instruct (free)", + "created": 1757612213, + "description": "Qwen3-Next-80B-A3B-Instruct is an instruction-tuned chat model in the Qwen3-Next series optimized for fast, stable responses without “thinking” traces. It targets complex tasks across reasoning, code generation, knowledge QA, and multilingual use, while remaining robust on alignment and formatting. Compared with prior Qwen3 instruct variants, it focuses on higher throughput and stability on ultra-long inputs and multi-turn dialogues, making it well-suited for RAG, tool use, and agentic workflows that require consistent final answers rather than visible chain-of-thought.\n\nThe model employs scaling-efficient training and decoding to improve parameter efficiency and inference speed, and has been validated on a broad set of public benchmarks where it reaches or approaches larger Qwen3 systems in several categories while outperforming earlier mid-sized baselines. It is best used as a general assistant, code helper, and long-context task solver in production settings where deterministic, instruction-following outputs are preferred.", + "context_length": 262144, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Qwen3", + "instruct_type": null + }, + "pricing": { + "prompt": "0", + "completion": "0", + "request": "0", + "image": "0", + "web_search": "0", + "internal_reasoning": "0" + }, + "top_provider": { + "context_length": 262144, + "max_completion_tokens": null, + "is_moderated": false + }, + "per_request_limits": null, + "supported_parameters": [ + "frequency_penalty", + "max_tokens", + "presence_penalty", + "response_format", + "stop", + "structured_outputs", + "temperature", + "tool_choice", + "tools", + "top_k", + "top_p" + ], + "default_parameters": {}, + "expiration_date": null }, { "id": "qwen/qwen3-next-80b-a3b-instruct", @@ -5085,7 +5648,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "meituan/longcat-flash-chat", @@ -5125,7 +5689,8 @@ "temperature", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "qwen/qwen-plus-2025-07-28", @@ -5175,7 +5740,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "qwen/qwen-plus-2025-07-28:thinking", @@ -5227,7 +5793,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "nvidia/nemotron-nano-9b-v2:free", @@ -5274,7 +5841,8 @@ "tools", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "nvidia/nemotron-nano-9b-v2", @@ -5327,7 +5895,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "moonshotai/kimi-k2-0905", @@ -5381,7 +5950,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "moonshotai/kimi-k2-0905:exacto", @@ -5429,7 +5999,8 @@ "tools", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "deepcogito/cogito-v2-preview-llama-70b", @@ -5486,7 +6057,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": "2026-02-04" }, { "id": "deepcogito/cogito-v2-preview-llama-109b-moe", @@ -5538,7 +6110,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": "2026-02-04" }, { "id": "stepfun-ai/step3", @@ -5586,7 +6159,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "qwen/qwen3-30b-a3b-thinking-2507", @@ -5637,7 +6211,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "x-ai/grok-code-fast-1", @@ -5688,7 +6263,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "nousresearch/hermes-4-70b", @@ -5740,7 +6316,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "nousresearch/hermes-4-405b", @@ -5762,8 +6339,8 @@ "instruct_type": null }, "pricing": { - "prompt": "0.0000003", - "completion": "0.0000012", + "prompt": "0.000001", + "completion": "0.000003", "request": "0", "image": "0", "web_search": "0", @@ -5771,7 +6348,7 @@ }, "top_provider": { "context_length": 131072, - "max_completion_tokens": 131072, + "max_completion_tokens": null, "is_moderated": false }, "per_request_limits": null, @@ -5783,65 +6360,12 @@ "reasoning", "repetition_penalty", "response_format", - "seed", - "stop", - "structured_outputs", "temperature", - "tool_choice", - "tools", "top_k", "top_p" ], - "default_parameters": {} - }, - { - "id": "google/gemini-2.5-flash-image-preview", - "canonical_slug": "google/gemini-2.5-flash-image-preview", - "hugging_face_id": "", - "name": "Google: Gemini 2.5 Flash Image Preview (Nano Banana)", - "created": 1756218977, - "description": "Gemini 2.5 Flash Image Preview, a.k.a. \"Nano Banana,\" is a state of the art image generation model with contextual understanding. It is capable of image generation, edits, and multi-turn conversations.", - "context_length": 32768, - "architecture": { - "modality": "text+image->text+image", - "input_modalities": [ - "image", - "text" - ], - "output_modalities": [ - "image", - "text" - ], - "tokenizer": "Gemini", - "instruct_type": null - }, - "pricing": { - "prompt": "0.0000003", - "completion": "0.0000025", - "request": "0", - "image": "0.001238", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 32768, - "max_completion_tokens": 32768, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "max_tokens", - "response_format", - "seed", - "structured_outputs", - "temperature", - "top_p" - ], - "default_parameters": { - "temperature": null, - "top_p": null, - "frequency_penalty": null - } + "default_parameters": {}, + "expiration_date": null }, { "id": "deepseek/deepseek-chat-v3.1", @@ -5897,7 +6421,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "openai/gpt-4o-audio-preview", @@ -5905,16 +6430,17 @@ "hugging_face_id": "", "name": "OpenAI: GPT-4o Audio", "created": 1755233061, - "description": "The gpt-4o-audio-preview model adds support for audio inputs as prompts. This enhancement allows the model to detect nuances within audio recordings and add depth to generated user experiences. Audio outputs are currently not supported. Audio tokens are priced at $40 per million input audio tokens.", + "description": "The gpt-4o-audio-preview model adds support for audio inputs as prompts. This enhancement allows the model to detect nuances within audio recordings and add depth to generated user experiences. Audio outputs are currently not supported. Audio tokens are priced at $40 per million input and $80 per million output audio tokens.", "context_length": 128000, "architecture": { - "modality": "text->text", + "modality": "text+audio->text+audio", "input_modalities": [ "audio", "text" ], "output_modalities": [ - "text" + "text", + "audio" ], "tokenizer": "GPT", "instruct_type": null @@ -5922,11 +6448,7 @@ "pricing": { "prompt": "0.0000025", "completion": "0.00001", - "request": "0", - "image": "0", - "audio": "0.00004", - "web_search": "0", - "internal_reasoning": "0" + "audio": "0.00004" }, "top_provider": { "context_length": 128000, @@ -5950,7 +6472,12 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": { + "temperature": null, + "top_p": null, + "frequency_penalty": null + }, + "expiration_date": null }, { "id": "mistralai/mistral-medium-3.1", @@ -5974,11 +6501,7 @@ }, "pricing": { "prompt": "0.0000004", - "completion": "0.000002", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.000002" }, "top_provider": { "context_length": 131072, @@ -6001,7 +6524,8 @@ ], "default_parameters": { "temperature": 0.3 - } + }, + "expiration_date": null }, { "id": "baidu/ernie-4.5-21b-a3b", @@ -6023,8 +6547,8 @@ "instruct_type": null }, "pricing": { - "prompt": "0.000000056", - "completion": "0.000000224", + "prompt": "0.00000007", + "completion": "0.00000028", "request": "0", "image": "0", "web_search": "0", @@ -6053,7 +6577,8 @@ "temperature": 0.8, "top_p": 0.8, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "baidu/ernie-4.5-vl-28b-a3b", @@ -6076,8 +6601,8 @@ "instruct_type": null }, "pricing": { - "prompt": "0.000000112", - "completion": "0.000000448", + "prompt": "0.00000014", + "completion": "0.00000056", "request": "0", "image": "0", "web_search": "0", @@ -6104,7 +6629,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "z-ai/glm-4.5v", @@ -6127,13 +6653,13 @@ "instruct_type": null }, "pricing": { - "prompt": "0.00000048", - "completion": "0.00000144", + "prompt": "0.0000006", + "completion": "0.0000018", "request": "0", "image": "0", "web_search": "0", "internal_reasoning": "0", - "input_cache_read": "0.000000088", + "input_cache_read": "0.00000011", "input_cache_write": "0" }, "top_provider": { @@ -6163,7 +6689,8 @@ "temperature": 0.75, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "ai21/jamba-mini-1.7", @@ -6207,7 +6734,8 @@ "tools", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "ai21/jamba-large-1.7", @@ -6251,7 +6779,8 @@ "tools", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "openai/gpt-5-chat", @@ -6262,7 +6791,7 @@ "description": "GPT-5 Chat is designed for advanced, natural, multimodal, and context-aware conversations for enterprise applications.", "context_length": 128000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "file", "image", @@ -6277,10 +6806,7 @@ "pricing": { "prompt": "0.00000125", "completion": "0.00001", - "request": "0", - "image": "0", "web_search": "0.01", - "internal_reasoning": "0", "input_cache_read": "0.000000125" }, "top_provider": { @@ -6295,7 +6821,8 @@ "seed", "structured_outputs" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "openai/gpt-5", @@ -6306,7 +6833,7 @@ "description": "GPT-5 is OpenAI’s most advanced model, offering major improvements in reasoning, code quality, and user experience. It is optimized for complex tasks that require step-by-step reasoning, instruction following, and accuracy in high-stakes use cases. It supports test-time routing features and advanced prompt understanding, including user-specified intent like \"think hard about this.\" Improvements include reductions in hallucination, sycophancy, and better performance in coding, writing, and health-related tasks.", "context_length": 400000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "text", "image", @@ -6321,10 +6848,7 @@ "pricing": { "prompt": "0.00000125", "completion": "0.00001", - "request": "0", - "image": "0", "web_search": "0.01", - "internal_reasoning": "0", "input_cache_read": "0.000000125" }, "top_provider": { @@ -6347,7 +6871,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "openai/gpt-5-mini", @@ -6358,7 +6883,7 @@ "description": "GPT-5 Mini is a compact version of GPT-5, designed to handle lighter-weight reasoning tasks. It provides the same instruction-following and safety-tuning benefits as GPT-5, but with reduced latency and cost. GPT-5 Mini is the successor to OpenAI's o4-mini model.", "context_length": 400000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "text", "image", @@ -6373,10 +6898,7 @@ "pricing": { "prompt": "0.00000025", "completion": "0.000002", - "request": "0", - "image": "0", "web_search": "0.01", - "internal_reasoning": "0", "input_cache_read": "0.000000025" }, "top_provider": { @@ -6395,7 +6917,8 @@ "tool_choice", "tools" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "openai/gpt-5-nano", @@ -6406,7 +6929,7 @@ "description": "GPT-5-Nano is the smallest and fastest variant in the GPT-5 system, optimized for developer tools, rapid interactions, and ultra-low latency environments. While limited in reasoning depth compared to its larger counterparts, it retains key instruction-following and safety features. It is the successor to GPT-4.1-nano and offers a lightweight option for cost-sensitive or real-time applications.", "context_length": 400000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "text", "image", @@ -6421,10 +6944,7 @@ "pricing": { "prompt": "0.00000005", "completion": "0.0000004", - "request": "0", - "image": "0", "web_search": "0.01", - "internal_reasoning": "0", "input_cache_read": "0.000000005" }, "top_provider": { @@ -6443,7 +6963,8 @@ "tool_choice", "tools" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "openai/gpt-oss-120b:free", @@ -6492,7 +7013,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "openai/gpt-oss-120b", @@ -6553,7 +7075,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "openai/gpt-oss-120b:exacto", @@ -6610,7 +7133,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "openai/gpt-oss-20b:free", @@ -6641,32 +7165,26 @@ }, "top_provider": { "context_length": 131072, - "max_completion_tokens": 131072, - "is_moderated": false + "max_completion_tokens": null, + "is_moderated": true }, "per_request_limits": null, "supported_parameters": [ - "frequency_penalty", "include_reasoning", "max_tokens", - "presence_penalty", "reasoning", - "repetition_penalty", - "response_format", "seed", "stop", - "structured_outputs", "temperature", "tool_choice", - "tools", - "top_k", - "top_p" + "tools" ], "default_parameters": { "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "openai/gpt-oss-20b", @@ -6688,8 +7206,8 @@ "instruct_type": null }, "pricing": { - "prompt": "0.00000003", - "completion": "0.00000014", + "prompt": "0.00000002", + "completion": "0.0000001", "request": "0", "image": "0", "web_search": "0", @@ -6697,7 +7215,7 @@ }, "top_provider": { "context_length": 131072, - "max_completion_tokens": null, + "max_completion_tokens": 131072, "is_moderated": false }, "per_request_limits": null, @@ -6725,7 +7243,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "anthropic/claude-opus-4.1", @@ -6736,7 +7255,7 @@ "description": "Claude Opus 4.1 is an updated version of Anthropic’s flagship model, offering improved performance in coding, reasoning, and agentic tasks. It achieves 74.5% on SWE-bench Verified and shows notable gains in multi-file code refactoring, debugging precision, and detail-oriented reasoning. The model supports extended thinking up to 64K tokens and is optimized for tasks involving research, data analysis, and tool-assisted reasoning.", "context_length": 200000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "image", "text", @@ -6760,7 +7279,7 @@ }, "top_provider": { "context_length": 200000, - "max_completion_tokens": null, + "max_completion_tokens": 32000, "is_moderated": true }, "per_request_limits": null, @@ -6781,7 +7300,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "mistralai/codestral-2508", @@ -6804,11 +7324,7 @@ }, "pricing": { "prompt": "0.0000003", - "completion": "0.0000009", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.0000009" }, "top_provider": { "context_length": 256000, @@ -6831,7 +7347,8 @@ ], "default_parameters": { "temperature": 0.3 - } + }, + "expiration_date": null }, { "id": "qwen/qwen3-coder-30b-a3b-instruct", @@ -6881,7 +7398,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "qwen/qwen3-30b-a3b-instruct-2507", @@ -6931,7 +7449,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "z-ai/glm-4.5", @@ -6970,7 +7489,6 @@ "frequency_penalty", "include_reasoning", "max_tokens", - "min_p", "presence_penalty", "reasoning", "repetition_penalty", @@ -6988,7 +7506,8 @@ "temperature": 0.75, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "z-ai/glm-4.5-air:free", @@ -7017,6 +7536,55 @@ "web_search": "0", "internal_reasoning": "0" }, + "top_provider": { + "context_length": 131072, + "max_completion_tokens": 96000, + "is_moderated": false + }, + "per_request_limits": null, + "supported_parameters": [ + "include_reasoning", + "max_tokens", + "reasoning", + "temperature", + "tool_choice", + "tools", + "top_p" + ], + "default_parameters": { + "temperature": 0.75, + "top_p": null, + "frequency_penalty": null + }, + "expiration_date": null + }, + { + "id": "z-ai/glm-4.5-air", + "canonical_slug": "z-ai/glm-4.5-air", + "hugging_face_id": "zai-org/GLM-4.5-Air", + "name": "Z.AI: GLM 4.5 Air", + "created": 1753471258, + "description": "GLM-4.5-Air is the lightweight variant of our latest flagship model family, also purpose-built for agent-centric applications. Like GLM-4.5, it adopts the Mixture-of-Experts (MoE) architecture but with a more compact parameter size. GLM-4.5-Air also supports hybrid inference modes, offering a \"thinking mode\" for advanced reasoning and tool use, and a \"non-thinking mode\" for real-time interaction. Users can control the reasoning behaviour with the `reasoning` `enabled` boolean. [Learn more in our docs](https://openrouter.ai/docs/use-cases/reasoning-tokens#enable-reasoning-with-default-config)", + "context_length": 131072, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Other", + "instruct_type": null + }, + "pricing": { + "prompt": "0.00000005", + "completion": "0.00000022", + "request": "0", + "image": "0", + "web_search": "0", + "internal_reasoning": "0" + }, "top_provider": { "context_length": 131072, "max_completion_tokens": 131072, @@ -7044,64 +7612,8 @@ "temperature": 0.75, "top_p": null, "frequency_penalty": null - } - }, - { - "id": "z-ai/glm-4.5-air", - "canonical_slug": "z-ai/glm-4.5-air", - "hugging_face_id": "zai-org/GLM-4.5-Air", - "name": "Z.AI: GLM 4.5 Air", - "created": 1753471258, - "description": "GLM-4.5-Air is the lightweight variant of our latest flagship model family, also purpose-built for agent-centric applications. Like GLM-4.5, it adopts the Mixture-of-Experts (MoE) architecture but with a more compact parameter size. GLM-4.5-Air also supports hybrid inference modes, offering a \"thinking mode\" for advanced reasoning and tool use, and a \"non-thinking mode\" for real-time interaction. Users can control the reasoning behaviour with the `reasoning` `enabled` boolean. [Learn more in our docs](https://openrouter.ai/docs/use-cases/reasoning-tokens#enable-reasoning-with-default-config)", - "context_length": 131072, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Other", - "instruct_type": null }, - "pricing": { - "prompt": "0.000000104", - "completion": "0.00000068", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0", - "input_cache_read": "0" - }, - "top_provider": { - "context_length": 131072, - "max_completion_tokens": 98304, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "frequency_penalty", - "include_reasoning", - "max_tokens", - "presence_penalty", - "reasoning", - "repetition_penalty", - "response_format", - "seed", - "stop", - "structured_outputs", - "temperature", - "tool_choice", - "tools", - "top_k", - "top_p" - ], - "default_parameters": { - "temperature": 0.75, - "top_p": null, - "frequency_penalty": null - } + "expiration_date": null }, { "id": "qwen/qwen3-235b-a22b-thinking-2507", @@ -7155,7 +7667,12 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": { + "temperature": null, + "top_p": null, + "frequency_penalty": null + }, + "expiration_date": null }, { "id": "z-ai/glm-4-32b", @@ -7201,7 +7718,8 @@ "temperature": 0.75, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "qwen/qwen3-coder:free", @@ -7240,7 +7758,6 @@ "frequency_penalty", "max_tokens", "presence_penalty", - "repetition_penalty", "seed", "stop", "temperature", @@ -7249,7 +7766,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "qwen/qwen3-coder", @@ -7304,7 +7822,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "qwen/qwen3-coder:exacto", @@ -7355,7 +7874,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "bytedance/ui-tars-1.5-7b", @@ -7395,7 +7915,6 @@ "frequency_penalty", "logit_bias", "max_tokens", - "min_p", "presence_penalty", "repetition_penalty", "seed", @@ -7404,7 +7923,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "google/gemini-2.5-flash-lite", @@ -7415,7 +7935,7 @@ "description": "Gemini 2.5 Flash-Lite is a lightweight reasoning model in the Gemini 2.5 family, optimized for ultra-low latency and cost efficiency. It offers improved throughput, faster token generation, and better performance across common benchmarks compared to earlier Flash models. By default, \"thinking\" (i.e. multi-pass reasoning) is disabled to prioritize speed, but developers can enable it via the [Reasoning API parameter](https://openrouter.ai/docs/use-cases/reasoning-tokens) to selectively trade off cost for intelligence. ", "context_length": 1048576, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file+audio+video->text", "input_modalities": [ "text", "image", @@ -7432,12 +7952,11 @@ "pricing": { "prompt": "0.0000001", "completion": "0.0000004", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0", + "image": "0.0000001", + "audio": "0.0000003", + "internal_reasoning": "0.0000004", "input_cache_read": "0.00000001", - "input_cache_write": "0.0000001833" + "input_cache_write": "0.00000008333333333333334" }, "top_provider": { "context_length": 1048576, @@ -7462,7 +7981,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "qwen/qwen3-235b-a22b-2507", @@ -7519,7 +8039,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "switchpoint/router", @@ -7542,11 +8063,7 @@ }, "pricing": { "prompt": "0.00000085", - "completion": "0.0000034", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.0000034" }, "top_provider": { "context_length": 131072, @@ -7564,7 +8081,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "moonshotai/kimi-k2:free", @@ -7605,7 +8123,8 @@ "stop", "temperature" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "moonshotai/kimi-k2", @@ -7627,8 +8146,8 @@ "instruct_type": null }, "pricing": { - "prompt": "0.000000456", - "completion": "0.00000184", + "prompt": "0.0000005", + "completion": "0.0000024", "request": "0", "image": "0", "web_search": "0", @@ -7636,7 +8155,7 @@ }, "top_provider": { "context_length": 131072, - "max_completion_tokens": 131072, + "max_completion_tokens": null, "is_moderated": false }, "per_request_limits": null, @@ -7658,56 +8177,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} - }, - { - "id": "thudm/glm-4.1v-9b-thinking", - "canonical_slug": "thudm/glm-4.1v-9b-thinking", - "hugging_face_id": "THUDM/GLM-4.1V-9B-Thinking", - "name": "THUDM: GLM 4.1V 9B Thinking", - "created": 1752244385, - "description": "GLM-4.1V-9B-Thinking is a 9B parameter vision-language model developed by THUDM, based on the GLM-4-9B foundation. It introduces a reasoning-centric \"thinking paradigm\" enhanced with reinforcement learning to improve multimodal reasoning, long-context understanding (up to 64K tokens), and complex problem solving. It achieves state-of-the-art performance among models in its class, outperforming even larger models like Qwen-2.5-VL-72B on a majority of benchmark tasks. ", - "context_length": 65536, - "architecture": { - "modality": "text+image->text", - "input_modalities": [ - "image", - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Other", - "instruct_type": null - }, - "pricing": { - "prompt": "0.000000028", - "completion": "0.0000001104", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 65536, - "max_completion_tokens": 8000, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "frequency_penalty", - "include_reasoning", - "max_tokens", - "presence_penalty", - "reasoning", - "repetition_penalty", - "seed", - "stop", - "temperature", - "top_k", - "top_p" - ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "mistralai/devstral-medium", @@ -7730,11 +8201,7 @@ }, "pricing": { "prompt": "0.0000004", - "completion": "0.000002", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.000002" }, "top_provider": { "context_length": 131072, @@ -7757,7 +8224,8 @@ ], "default_parameters": { "temperature": 0.3 - } + }, + "expiration_date": null }, { "id": "mistralai/devstral-small", @@ -7766,7 +8234,7 @@ "name": "Mistral: Devstral Small 1.1", "created": 1752160751, "description": "Devstral Small 1.1 is a 24B parameter open-weight language model for software engineering agents, developed by Mistral AI in collaboration with All Hands AI. Finetuned from Mistral Small 3.1 and released under the Apache 2.0 license, it features a 128k token context window and supports both Mistral-style function calling and XML output formats.\n\nDesigned for agentic coding workflows, Devstral Small 1.1 is optimized for tasks such as codebase exploration, multi-file edits, and integration into autonomous development agents like OpenHands and Cline. It achieves 53.6% on SWE-Bench Verified, surpassing all other open models on this benchmark, while remaining lightweight enough to run on a single 4090 GPU or Apple silicon machine. The model uses a Tekken tokenizer with a 131k vocabulary and is deployable via vLLM, Transformers, Ollama, LM Studio, and other OpenAI-compatible runtimes.\n", - "context_length": 128000, + "context_length": 131072, "architecture": { "modality": "text->text", "input_modalities": [ @@ -7779,15 +8247,11 @@ "instruct_type": null }, "pricing": { - "prompt": "0.00000007", - "completion": "0.00000028", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "prompt": "0.0000001", + "completion": "0.0000003" }, "top_provider": { - "context_length": 128000, + "context_length": 131072, "max_completion_tokens": null, "is_moderated": false }, @@ -7795,9 +8259,7 @@ "supported_parameters": [ "frequency_penalty", "max_tokens", - "min_p", "presence_penalty", - "repetition_penalty", "response_format", "seed", "stop", @@ -7805,12 +8267,12 @@ "temperature", "tool_choice", "tools", - "top_k", "top_p" ], "default_parameters": { "temperature": 0.3 - } + }, + "expiration_date": null }, { "id": "cognitivecomputations/dolphin-mistral-24b-venice-edition:free", @@ -7856,7 +8318,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "x-ai/grok-4", @@ -7907,7 +8370,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "google/gemma-3n-e2b-it:free", @@ -7930,11 +8394,7 @@ }, "pricing": { "prompt": "0", - "completion": "0", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0" }, "top_provider": { "context_length": 8192, @@ -7952,7 +8412,8 @@ "temperature", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "tencent/hunyuan-a13b-instruct", @@ -7997,7 +8458,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "tngtech/deepseek-r1t2-chimera:free", @@ -8045,7 +8507,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "tngtech/deepseek-r1t2-chimera", @@ -8097,7 +8560,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "morph/morph-v3-large", @@ -8141,7 +8605,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "morph/morph-v3-fast", @@ -8185,7 +8650,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "baidu/ernie-4.5-vl-424b-a47b", @@ -8208,8 +8674,8 @@ "instruct_type": null }, "pricing": { - "prompt": "0.000000336", - "completion": "0.000001", + "prompt": "0.00000042", + "completion": "0.00000125", "request": "0", "image": "0", "web_search": "0", @@ -8234,7 +8700,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "baidu/ernie-4.5-300b-a47b", @@ -8256,8 +8723,8 @@ "instruct_type": null }, "pricing": { - "prompt": "0.000000224", - "completion": "0.00000088", + "prompt": "0.00000028", + "completion": "0.0000011", "request": "0", "image": "0", "web_search": "0", @@ -8282,7 +8749,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "inception/mercury", @@ -8305,11 +8773,7 @@ }, "pricing": { "prompt": "0.00000025", - "completion": "0.000001", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.000001" }, "top_provider": { "context_length": 128000, @@ -8334,7 +8798,8 @@ "temperature": 0, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "mistralai/mistral-small-3.2-24b-instruct", @@ -8389,7 +8854,8 @@ ], "default_parameters": { "temperature": 0.3 - } + }, + "expiration_date": null }, { "id": "minimax/minimax-m1", @@ -8439,7 +8905,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "google/gemini-2.5-flash", @@ -8450,7 +8917,7 @@ "description": "Gemini 2.5 Flash is Google's state-of-the-art workhorse model, specifically designed for advanced reasoning, coding, mathematics, and scientific tasks. It includes built-in \"thinking\" capabilities, enabling it to provide responses with greater accuracy and nuanced context handling. \n\nAdditionally, Gemini 2.5 Flash is configurable through the \"max tokens for reasoning\" parameter, as described in the documentation (https://openrouter.ai/docs/use-cases/reasoning-tokens#max-tokens-for-reasoning).", "context_length": 1048576, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file+audio+video->text", "input_modalities": [ "file", "image", @@ -8467,13 +8934,11 @@ "pricing": { "prompt": "0.0000003", "completion": "0.0000025", - "request": "0", - "image": "0.001238", + "image": "0.0000003", "audio": "0.000001", - "web_search": "0", - "internal_reasoning": "0", + "internal_reasoning": "0.0000025", "input_cache_read": "0.00000003", - "input_cache_write": "0.0000003833" + "input_cache_write": "0.00000008333333333333334" }, "top_provider": { "context_length": 1048576, @@ -8498,7 +8963,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "google/gemini-2.5-pro", @@ -8509,7 +8975,7 @@ "description": "Gemini 2.5 Pro is Google’s state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs “thinking” capabilities, enabling it to reason through responses with enhanced accuracy and nuanced context handling. Gemini 2.5 Pro achieves top-tier performance on multiple benchmarks, including first-place positioning on the LMArena leaderboard, reflecting superior human-preference alignment and complex problem-solving abilities.", "context_length": 1048576, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file+audio+video->text", "input_modalities": [ "text", "image", @@ -8526,12 +8992,11 @@ "pricing": { "prompt": "0.00000125", "completion": "0.00001", - "request": "0", - "image": "0.00516", - "web_search": "0", - "internal_reasoning": "0", + "image": "0.00000125", + "audio": "0.00000125", + "internal_reasoning": "0.00001", "input_cache_read": "0.000000125", - "input_cache_write": "0.000001625" + "input_cache_write": "0.000000375" }, "top_provider": { "context_length": 1048576, @@ -8556,7 +9021,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "moonshotai/kimi-dev-72b", @@ -8601,7 +9067,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "openai/o3-pro", @@ -8612,7 +9079,7 @@ "description": "The o-series of models are trained with reinforcement learning to think before they answer and perform complex reasoning. The o3-pro model uses more compute to think harder and provide consistently better answers.\n\nNote that BYOK is required for this model. Set up here: https://openrouter.ai/settings/integrations", "context_length": 200000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "text", "file", @@ -8627,10 +9094,7 @@ "pricing": { "prompt": "0.00002", "completion": "0.00008", - "request": "0", - "image": "0.0153", - "web_search": "0.01", - "internal_reasoning": "0" + "web_search": "0.01" }, "top_provider": { "context_length": 200000, @@ -8648,7 +9112,12 @@ "tool_choice", "tools" ], - "default_parameters": {} + "default_parameters": { + "temperature": null, + "top_p": null, + "frequency_penalty": null + }, + "expiration_date": null }, { "id": "x-ai/grok-3-mini", @@ -8699,7 +9168,12 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": { + "temperature": null, + "top_p": null, + "frequency_penalty": null + }, + "expiration_date": null }, { "id": "x-ai/grok-3", @@ -8750,7 +9224,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "google/gemini-2.5-pro-preview", @@ -8761,7 +9236,7 @@ "description": "Gemini 2.5 Pro is Google’s state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs “thinking” capabilities, enabling it to reason through responses with enhanced accuracy and nuanced context handling. Gemini 2.5 Pro achieves top-tier performance on multiple benchmarks, including first-place positioning on the LMArena leaderboard, reflecting superior human-preference alignment and complex problem-solving abilities.\n", "context_length": 1048576, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file+audio->text", "input_modalities": [ "file", "image", @@ -8777,12 +9252,11 @@ "pricing": { "prompt": "0.00000125", "completion": "0.00001", - "request": "0", - "image": "0.00516", - "web_search": "0", - "internal_reasoning": "0", - "input_cache_read": "0.00000031", - "input_cache_write": "0.000001625" + "image": "0.00000125", + "audio": "0.00000125", + "internal_reasoning": "0.00001", + "input_cache_read": "0.000000125", + "input_cache_write": "0.000000375" }, "top_provider": { "context_length": 1048576, @@ -8803,59 +9277,8 @@ "tools", "top_p" ], - "default_parameters": {} - }, - { - "id": "deepseek/deepseek-r1-0528-qwen3-8b", - "canonical_slug": "deepseek/deepseek-r1-0528-qwen3-8b", - "hugging_face_id": "deepseek-ai/deepseek-r1-0528-qwen3-8b", - "name": "DeepSeek: DeepSeek R1 0528 Qwen3 8B", - "created": 1748538543, - "description": "DeepSeek-R1-0528 is a lightly upgraded release of DeepSeek R1 that taps more compute and smarter post-training tricks, pushing its reasoning and inference to the brink of flagship models like O3 and Gemini 2.5 Pro.\nIt now tops math, programming, and logic leaderboards, showcasing a step-change in depth-of-thought.\nThe distilled variant, DeepSeek-R1-0528-Qwen3-8B, transfers this chain-of-thought into an 8 B-parameter form, beating standard Qwen3 8B by +10 pp and tying the 235 B “thinking” giant on AIME 2024.", - "context_length": 128000, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Qwen", - "instruct_type": "deepseek-r1" - }, - "pricing": { - "prompt": "0.000000048", - "completion": "0.000000072", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 128000, - "max_completion_tokens": 32000, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "frequency_penalty", - "include_reasoning", - "max_tokens", - "presence_penalty", - "reasoning", - "repetition_penalty", - "seed", - "stop", - "temperature", - "top_k", - "top_p" - ], - "default_parameters": { - "temperature": null, - "top_p": null, - "frequency_penalty": null - } + "default_parameters": {}, + "expiration_date": null }, { "id": "deepseek/deepseek-r1-0528:free", @@ -8878,11 +9301,7 @@ }, "pricing": { "prompt": "0", - "completion": "0", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0" }, "top_provider": { "context_length": 163840, @@ -8899,7 +9318,12 @@ "repetition_penalty", "temperature" ], - "default_parameters": {} + "default_parameters": { + "temperature": null, + "top_p": null, + "frequency_penalty": null + }, + "expiration_date": null }, { "id": "deepseek/deepseek-r1-0528", @@ -8930,7 +9354,7 @@ }, "top_provider": { "context_length": 163840, - "max_completion_tokens": 163840, + "max_completion_tokens": 65536, "is_moderated": false }, "per_request_limits": null, @@ -8955,7 +9379,12 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": { + "temperature": null, + "top_p": null, + "frequency_penalty": null + }, + "expiration_date": null }, { "id": "anthropic/claude-opus-4", @@ -8966,7 +9395,7 @@ "description": "Claude Opus 4 is benchmarked as the world’s best coding model, at time of release, bringing sustained performance on complex, long-running tasks and agent workflows. It sets new benchmarks in software engineering, achieving leading results on SWE-bench (72.5%) and Terminal-bench (43.2%). Opus 4 supports extended, agentic workflows, handling thousands of task steps continuously for hours without degradation. \n\nRead more at the [blog post here](https://www.anthropic.com/news/claude-4)", "context_length": 200000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "image", "text", @@ -9009,7 +9438,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "anthropic/claude-sonnet-4", @@ -9020,7 +9450,7 @@ "description": "Claude Sonnet 4 significantly enhances the capabilities of its predecessor, Sonnet 3.7, excelling in both coding and reasoning tasks with improved precision and controllability. Achieving state-of-the-art performance on SWE-bench (72.7%), Sonnet 4 balances capability and computational efficiency, making it suitable for a broad range of applications from routine coding tasks to complex software development projects. Key enhancements include improved autonomous codebase navigation, reduced error rates in agent-driven workflows, and increased reliability in following intricate instructions. Sonnet 4 is optimized for practical everyday use, providing advanced reasoning capabilities while maintaining efficiency and responsiveness in diverse internal and external scenarios.\n\nRead more at the [blog post here](https://www.anthropic.com/news/claude-4)", "context_length": 1000000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "image", "text", @@ -9063,57 +9493,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } - }, - { - "id": "mistralai/devstral-small-2505", - "canonical_slug": "mistralai/devstral-small-2505", - "hugging_face_id": "mistralai/Devstral-Small-2505", - "name": "Mistral: Devstral Small 2505", - "created": 1747837379, - "description": "Devstral-Small-2505 is a 24B parameter agentic LLM fine-tuned from Mistral-Small-3.1, jointly developed by Mistral AI and All Hands AI for advanced software engineering tasks. It is optimized for codebase exploration, multi-file editing, and integration into coding agents, achieving state-of-the-art results on SWE-Bench Verified (46.8%).\n\nDevstral supports a 128k context window and uses a custom Tekken tokenizer. It is text-only, with the vision encoder removed, and is suitable for local deployment on high-end consumer hardware (e.g., RTX 4090, 32GB RAM Macs). Devstral is best used in agentic workflows via the OpenHands scaffold and is compatible with inference frameworks like vLLM, Transformers, and Ollama. It is released under the Apache 2.0 license.", - "context_length": 128000, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Mistral", - "instruct_type": null }, - "pricing": { - "prompt": "0.00000006", - "completion": "0.00000012", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 128000, - "max_completion_tokens": null, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "frequency_penalty", - "max_tokens", - "min_p", - "presence_penalty", - "repetition_penalty", - "response_format", - "seed", - "stop", - "temperature", - "top_k", - "top_p" - ], - "default_parameters": { - "temperature": 0.3 - } + "expiration_date": null }, { "id": "google/gemma-3n-e4b-it:free", @@ -9136,11 +9517,7 @@ }, "pricing": { "prompt": "0", - "completion": "0", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0" }, "top_provider": { "context_length": 8192, @@ -9158,7 +9535,8 @@ "temperature", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "google/gemma-3n-e4b-it", @@ -9205,54 +9583,8 @@ "top_k", "top_p" ], - "default_parameters": {} - }, - { - "id": "openai/codex-mini", - "canonical_slug": "openai/codex-mini", - "hugging_face_id": "", - "name": "OpenAI: Codex Mini", - "created": 1747409761, - "description": "codex-mini-latest is a fine-tuned version of o4-mini specifically for use in Codex CLI. For direct use in the API, we recommend starting with gpt-4.1.", - "context_length": 200000, - "architecture": { - "modality": "text+image->text", - "input_modalities": [ - "image", - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "GPT", - "instruct_type": null - }, - "pricing": { - "prompt": "0.0000015", - "completion": "0.000006", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0", - "input_cache_read": "0.000000375" - }, - "top_provider": { - "context_length": 200000, - "max_completion_tokens": 100000, - "is_moderated": true - }, - "per_request_limits": null, - "supported_parameters": [ - "include_reasoning", - "max_tokens", - "reasoning", - "response_format", - "seed", - "structured_outputs", - "tool_choice", - "tools" - ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "nousresearch/deephermes-3-mistral-24b-preview", @@ -9304,7 +9636,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "mistralai/mistral-medium-3", @@ -9328,11 +9661,7 @@ }, "pricing": { "prompt": "0.0000004", - "completion": "0.000002", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.000002" }, "top_provider": { "context_length": 131072, @@ -9355,7 +9684,8 @@ ], "default_parameters": { "temperature": 0.3 - } + }, + "expiration_date": null }, { "id": "google/gemini-2.5-pro-preview-05-06", @@ -9366,7 +9696,7 @@ "description": "Gemini 2.5 Pro is Google’s state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs “thinking” capabilities, enabling it to reason through responses with enhanced accuracy and nuanced context handling. Gemini 2.5 Pro achieves top-tier performance on multiple benchmarks, including first-place positioning on the LMArena leaderboard, reflecting superior human-preference alignment and complex problem-solving abilities.", "context_length": 1048576, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file+audio+video->text", "input_modalities": [ "text", "image", @@ -9383,12 +9713,11 @@ "pricing": { "prompt": "0.00000125", "completion": "0.00001", - "request": "0", - "image": "0.00516", - "web_search": "0", - "internal_reasoning": "0", - "input_cache_read": "0.00000031", - "input_cache_write": "0.000001625" + "image": "0.00000125", + "audio": "0.00000125", + "internal_reasoning": "0.00001", + "input_cache_read": "0.000000125", + "input_cache_write": "0.000000375" }, "top_provider": { "context_length": 1048576, @@ -9413,7 +9742,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "arcee-ai/spotlight", @@ -9461,7 +9791,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "arcee-ai/maestro-reasoning", @@ -9508,7 +9839,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "arcee-ai/virtuoso-large", @@ -9557,7 +9889,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "arcee-ai/coder-large", @@ -9604,57 +9937,8 @@ "top_k", "top_p" ], - "default_parameters": {} - }, - { - "id": "microsoft/phi-4-reasoning-plus", - "canonical_slug": "microsoft/phi-4-reasoning-plus-04-30", - "hugging_face_id": "microsoft/Phi-4-reasoning-plus", - "name": "Microsoft: Phi 4 Reasoning Plus", - "created": 1746130961, - "description": "Phi-4-reasoning-plus is an enhanced 14B parameter model from Microsoft, fine-tuned from Phi-4 with additional reinforcement learning to boost accuracy on math, science, and code reasoning tasks. It uses the same dense decoder-only transformer architecture as Phi-4, but generates longer, more comprehensive outputs structured into a step-by-step reasoning trace and final answer.\n\nWhile it offers improved benchmark scores over Phi-4-reasoning across tasks like AIME, OmniMath, and HumanEvalPlus, its responses are typically ~50% longer, resulting in higher latency. Designed for English-only applications, it is well-suited for structured reasoning workflows where output quality takes priority over response speed.", - "context_length": 32768, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Other", - "instruct_type": null - }, - "pricing": { - "prompt": "0.00000007", - "completion": "0.00000035", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 32768, - "max_completion_tokens": null, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "frequency_penalty", - "include_reasoning", - "max_tokens", - "min_p", - "presence_penalty", - "reasoning", - "repetition_penalty", - "response_format", - "seed", - "stop", - "temperature", - "top_k", - "top_p" - ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "inception/mercury-coder", @@ -9677,11 +9961,7 @@ }, "pricing": { "prompt": "0.00000025", - "completion": "0.000001", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.000001" }, "top_provider": { "context_length": 128000, @@ -9706,7 +9986,8 @@ "temperature": 0, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "qwen/qwen3-4b:free", @@ -9756,55 +10037,8 @@ "top_k", "top_p" ], - "default_parameters": {} - }, - { - "id": "deepseek/deepseek-prover-v2", - "canonical_slug": "deepseek/deepseek-prover-v2", - "hugging_face_id": "deepseek-ai/DeepSeek-Prover-V2-671B", - "name": "DeepSeek: DeepSeek Prover V2", - "created": 1746013094, - "description": "DeepSeek Prover V2 is a 671B parameter model, speculated to be geared towards logic and mathematics. Likely an upgrade from [DeepSeek-Prover-V1.5](https://huggingface.co/deepseek-ai/DeepSeek-Prover-V1.5-RL) Not much is known about the model yet, as DeepSeek released it on Hugging Face without an announcement or description.", - "context_length": 163840, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "DeepSeek", - "instruct_type": null - }, - "pricing": { - "prompt": "0.0000005", - "completion": "0.00000218", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 163840, - "max_completion_tokens": null, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "frequency_penalty", - "max_tokens", - "min_p", - "presence_penalty", - "repetition_penalty", - "response_format", - "seed", - "stop", - "temperature", - "top_k", - "top_p" - ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "meta-llama/llama-guard-4-12b", @@ -9854,7 +10088,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "qwen/qwen3-30b-a3b", @@ -9907,7 +10142,12 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": { + "temperature": null, + "top_p": null, + "frequency_penalty": null + }, + "expiration_date": null }, { "id": "qwen/qwen3-8b", @@ -9916,7 +10156,7 @@ "name": "Qwen: Qwen3 8B", "created": 1745876632, "description": "Qwen3-8B is a dense 8.2B parameter causal language model from the Qwen3 series, designed for both reasoning-heavy tasks and efficient dialogue. It supports seamless switching between \"thinking\" mode for math, coding, and logical inference, and \"non-thinking\" mode for general conversation. The model is fine-tuned for instruction-following, agent integration, creative writing, and multilingual use across 100+ languages and dialects. It natively supports a 32K token context window and can extend to 131K tokens with YaRN scaling.", - "context_length": 128000, + "context_length": 32000, "architecture": { "modality": "text->text", "input_modalities": [ @@ -9929,16 +10169,17 @@ "instruct_type": "qwen3" }, "pricing": { - "prompt": "0.000000028", - "completion": "0.0000001104", + "prompt": "0.00000005", + "completion": "0.00000025", "request": "0", "image": "0", "web_search": "0", - "internal_reasoning": "0" + "internal_reasoning": "0", + "input_cache_read": "0" }, "top_provider": { - "context_length": 128000, - "max_completion_tokens": 20000, + "context_length": 32000, + "max_completion_tokens": 8192, "is_moderated": false }, "per_request_limits": null, @@ -9952,7 +10193,6 @@ "reasoning", "repetition_penalty", "response_format", - "seed", "stop", "structured_outputs", "temperature", @@ -9962,7 +10202,12 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": { + "temperature": null, + "top_p": null, + "frequency_penalty": null + }, + "expiration_date": null }, { "id": "qwen/qwen3-14b", @@ -10015,7 +10260,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "qwen/qwen3-32b", @@ -10070,7 +10316,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "qwen/qwen3-235b-a22b", @@ -10092,8 +10339,8 @@ "instruct_type": "qwen3" }, "pricing": { - "prompt": "0.00000018", - "completion": "0.00000054", + "prompt": "0.0000002", + "completion": "0.0000006", "request": "0", "image": "0", "web_search": "0", @@ -10101,7 +10348,7 @@ }, "top_provider": { "context_length": 40960, - "max_completion_tokens": 40960, + "max_completion_tokens": null, "is_moderated": false }, "per_request_limits": null, @@ -10126,7 +10373,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "tngtech/deepseek-r1t-chimera:free", @@ -10174,7 +10422,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "tngtech/deepseek-r1t-chimera", @@ -10224,7 +10473,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "openai/o4-mini-high", @@ -10235,7 +10485,7 @@ "description": "OpenAI o4-mini-high is the same model as [o4-mini](/openai/o4-mini) with reasoning_effort set to high. \n\nOpenAI o4-mini is a compact reasoning model in the o-series, optimized for fast, cost-efficient performance while retaining strong multimodal and agentic capabilities. It supports tool use and demonstrates competitive reasoning and coding performance across benchmarks like AIME (99.5% with Python) and SWE-bench, outperforming its predecessor o3-mini and even approaching o3 in some domains.\n\nDespite its smaller size, o4-mini exhibits high accuracy in STEM tasks, visual problem solving (e.g., MathVista, MMMU), and code editing. It is especially well-suited for high-throughput scenarios where latency or cost is critical. Thanks to its efficient architecture and refined reinforcement learning training, o4-mini can chain tools, generate structured outputs, and solve multi-step tasks with minimal delay—often in under a minute.", "context_length": 200000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "image", "text", @@ -10244,16 +10494,13 @@ "output_modalities": [ "text" ], - "tokenizer": "Other", + "tokenizer": "GPT", "instruct_type": null }, "pricing": { "prompt": "0.0000011", "completion": "0.0000044", - "request": "0", - "image": "0.0008415", "web_search": "0.01", - "internal_reasoning": "0", "input_cache_read": "0.000000275" }, "top_provider": { @@ -10272,7 +10519,12 @@ "tool_choice", "tools" ], - "default_parameters": {} + "default_parameters": { + "temperature": null, + "top_p": null, + "frequency_penalty": null + }, + "expiration_date": null }, { "id": "openai/o3", @@ -10283,7 +10535,7 @@ "description": "o3 is a well-rounded and powerful model across domains. It sets a new standard for math, science, coding, and visual reasoning tasks. It also excels at technical writing and instruction-following. Use it to think through multi-step problems that involve analysis across text, code, and images. ", "context_length": 200000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "image", "text", @@ -10298,10 +10550,7 @@ "pricing": { "prompt": "0.000002", "completion": "0.000008", - "request": "0", - "image": "0.00153", "web_search": "0.01", - "internal_reasoning": "0", "input_cache_read": "0.0000005" }, "top_provider": { @@ -10320,7 +10569,8 @@ "tool_choice", "tools" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "openai/o4-mini", @@ -10331,7 +10581,7 @@ "description": "OpenAI o4-mini is a compact reasoning model in the o-series, optimized for fast, cost-efficient performance while retaining strong multimodal and agentic capabilities. It supports tool use and demonstrates competitive reasoning and coding performance across benchmarks like AIME (99.5% with Python) and SWE-bench, outperforming its predecessor o3-mini and even approaching o3 in some domains.\n\nDespite its smaller size, o4-mini exhibits high accuracy in STEM tasks, visual problem solving (e.g., MathVista, MMMU), and code editing. It is especially well-suited for high-throughput scenarios where latency or cost is critical. Thanks to its efficient architecture and refined reinforcement learning training, o4-mini can chain tools, generate structured outputs, and solve multi-step tasks with minimal delay—often in under a minute.", "context_length": 200000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "image", "text", @@ -10346,10 +10596,7 @@ "pricing": { "prompt": "0.0000011", "completion": "0.0000044", - "request": "0", - "image": "0.0008415", "web_search": "0.01", - "internal_reasoning": "0", "input_cache_read": "0.000000275" }, "top_provider": { @@ -10368,7 +10615,8 @@ "tool_choice", "tools" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "qwen/qwen2.5-coder-7b-instruct", @@ -10414,7 +10662,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "openai/gpt-4.1", @@ -10425,7 +10674,7 @@ "description": "GPT-4.1 is a flagship large language model optimized for advanced instruction following, real-world software engineering, and long-context reasoning. It supports a 1 million token context window and outperforms GPT-4o and GPT-4.5 across coding (54.6% SWE-bench Verified), instruction compliance (87.4% IFEval), and multimodal understanding benchmarks. It is tuned for precise code diffs, agent reliability, and high recall in large document contexts, making it ideal for agents, IDE tooling, and enterprise knowledge retrieval.", "context_length": 1047576, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "image", "text", @@ -10440,10 +10689,7 @@ "pricing": { "prompt": "0.000002", "completion": "0.000008", - "request": "0", - "image": "0", "web_search": "0.01", - "internal_reasoning": "0", "input_cache_read": "0.0000005" }, "top_provider": { @@ -10457,10 +10703,13 @@ "response_format", "seed", "structured_outputs", + "temperature", "tool_choice", - "tools" + "tools", + "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "openai/gpt-4.1-mini", @@ -10471,7 +10720,7 @@ "description": "GPT-4.1 Mini is a mid-sized model delivering performance competitive with GPT-4o at substantially lower latency and cost. It retains a 1 million token context window and scores 45.1% on hard instruction evals, 35.8% on MultiChallenge, and 84.1% on IFEval. Mini also shows strong coding ability (e.g., 31.6% on Aider’s polyglot diff benchmark) and vision understanding, making it suitable for interactive applications with tight performance constraints.", "context_length": 1047576, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "image", "text", @@ -10486,10 +10735,7 @@ "pricing": { "prompt": "0.0000004", "completion": "0.0000016", - "request": "0", - "image": "0", "web_search": "0.01", - "internal_reasoning": "0", "input_cache_read": "0.0000001" }, "top_provider": { @@ -10503,10 +10749,13 @@ "response_format", "seed", "structured_outputs", + "temperature", "tool_choice", - "tools" + "tools", + "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "openai/gpt-4.1-nano", @@ -10517,7 +10766,7 @@ "description": "For tasks that demand low latency, GPT‑4.1 nano is the fastest and cheapest model in the GPT-4.1 series. It delivers exceptional performance at a small size with its 1 million token context window, and scores 80.1% on MMLU, 50.3% on GPQA, and 9.8% on Aider polyglot coding – even higher than GPT‑4o mini. It’s ideal for tasks like classification or autocompletion.", "context_length": 1047576, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "image", "text", @@ -10532,10 +10781,7 @@ "pricing": { "prompt": "0.0000001", "completion": "0.0000004", - "request": "0", - "image": "0", "web_search": "0.01", - "internal_reasoning": "0", "input_cache_read": "0.000000025" }, "top_provider": { @@ -10549,10 +10795,13 @@ "response_format", "seed", "structured_outputs", + "temperature", "tool_choice", - "tools" + "tools", + "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "eleutherai/llemma_7b", @@ -10575,11 +10824,7 @@ }, "pricing": { "prompt": "0.0000008", - "completion": "0.0000012", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.0000012" }, "top_provider": { "context_length": 4096, @@ -10599,7 +10844,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "alfredpros/codellama-7b-instruct-solidity", @@ -10622,11 +10868,7 @@ }, "pricing": { "prompt": "0.0000008", - "completion": "0.0000012", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.0000012" }, "top_provider": { "context_length": 4096, @@ -10646,57 +10888,8 @@ "top_k", "top_p" ], - "default_parameters": {} - }, - { - "id": "arliai/qwq-32b-arliai-rpr-v1", - "canonical_slug": "arliai/qwq-32b-arliai-rpr-v1", - "hugging_face_id": "ArliAI/QwQ-32B-ArliAI-RpR-v1", - "name": "ArliAI: QwQ 32B RpR v1", - "created": 1744555982, - "description": "QwQ-32B-ArliAI-RpR-v1 is a 32B parameter model fine-tuned from Qwen/QwQ-32B using a curated creative writing and roleplay dataset originally developed for the RPMax series. It is designed to maintain coherence and reasoning across long multi-turn conversations by introducing explicit reasoning steps per dialogue turn, generated and refined using the base model itself.\n\nThe model was trained using RS-QLORA+ on 8K sequence lengths and supports up to 128K context windows (with practical performance around 32K). It is optimized for creative roleplay and dialogue generation, with an emphasis on minimizing cross-context repetition while preserving stylistic diversity.", - "context_length": 32768, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Other", - "instruct_type": "deepseek-r1" - }, - "pricing": { - "prompt": "0.00000003", - "completion": "0.00000011", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 32768, - "max_completion_tokens": 32768, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "frequency_penalty", - "include_reasoning", - "max_tokens", - "presence_penalty", - "reasoning", - "repetition_penalty", - "response_format", - "seed", - "stop", - "structured_outputs", - "temperature", - "top_k", - "top_p" - ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "x-ai/grok-3-mini-beta", @@ -10746,7 +10939,12 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": { + "temperature": null, + "top_p": null, + "frequency_penalty": null + }, + "expiration_date": null }, { "id": "x-ai/grok-3-beta", @@ -10796,7 +10994,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "nvidia/llama-3.1-nemotron-ultra-253b-v1", @@ -10844,7 +11043,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "meta-llama/llama-4-maverick", @@ -10897,7 +11097,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "meta-llama/llama-4-scout", @@ -10950,7 +11151,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "qwen/qwen2.5-vl-32b-instruct", @@ -11003,7 +11205,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "deepseek/deepseek-chat-v3-0324", @@ -11025,17 +11228,16 @@ "instruct_type": null }, "pricing": { - "prompt": "0.0000002", - "completion": "0.00000088", + "prompt": "0.00000019", + "completion": "0.00000087", "request": "0", "image": "0", "web_search": "0", - "internal_reasoning": "0", - "input_cache_read": "0.000000106" + "internal_reasoning": "0" }, "top_provider": { "context_length": 163840, - "max_completion_tokens": null, + "max_completion_tokens": 65536, "is_moderated": false }, "per_request_limits": null, @@ -11059,7 +11261,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "openai/o1-pro", @@ -11070,7 +11273,7 @@ "description": "The o1 series of models are trained with reinforcement learning to think before they answer and perform complex reasoning. The o1-pro model uses more compute to think harder and provide consistently better answers.", "context_length": 200000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "text", "image", @@ -11084,11 +11287,7 @@ }, "pricing": { "prompt": "0.00015", - "completion": "0.0006", - "request": "0", - "image": "0.21675", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.0006" }, "top_provider": { "context_length": 200000, @@ -11104,7 +11303,8 @@ "seed", "structured_outputs" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "mistralai/mistral-small-3.1-24b-instruct:free", @@ -11155,7 +11355,8 @@ ], "default_parameters": { "temperature": 0.3 - } + }, + "expiration_date": null }, { "id": "mistralai/mistral-small-3.1-24b-instruct", @@ -11208,7 +11409,8 @@ ], "default_parameters": { "temperature": 0.3 - } + }, + "expiration_date": null }, { "id": "allenai/olmo-2-0325-32b-instruct", @@ -11231,11 +11433,7 @@ }, "pricing": { "prompt": "0.00000005", - "completion": "0.0000002", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.0000002" }, "top_provider": { "context_length": 128000, @@ -11244,7 +11442,8 @@ }, "per_request_limits": null, "supported_parameters": [], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "google/gemma-3-4b-it:free", @@ -11268,11 +11467,7 @@ }, "pricing": { "prompt": "0", - "completion": "0", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0" }, "top_provider": { "context_length": 32768, @@ -11284,11 +11479,12 @@ "max_tokens", "response_format", "seed", - "structured_outputs", + "stop", "temperature", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "google/gemma-3-4b-it", @@ -11337,7 +11533,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "google/gemma-3-12b-it:free", @@ -11361,11 +11558,7 @@ }, "pricing": { "prompt": "0", - "completion": "0", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0" }, "top_provider": { "context_length": 32768, @@ -11376,10 +11569,12 @@ "supported_parameters": [ "max_tokens", "seed", + "stop", "temperature", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "google/gemma-3-12b-it", @@ -11430,7 +11625,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "cohere/command-a", @@ -11477,7 +11673,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "openai/gpt-4o-mini-search-preview", @@ -11501,10 +11698,7 @@ "pricing": { "prompt": "0.00000015", "completion": "0.0000006", - "request": "0.0275", - "image": "0.000217", - "web_search": "0", - "internal_reasoning": "0" + "web_search": "0.0275" }, "top_provider": { "context_length": 128000, @@ -11518,7 +11712,8 @@ "structured_outputs", "web_search_options" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "openai/gpt-4o-search-preview", @@ -11542,10 +11737,7 @@ "pricing": { "prompt": "0.0000025", "completion": "0.00001", - "request": "0.035", - "image": "0.003613", - "web_search": "0", - "internal_reasoning": "0" + "web_search": "0.035" }, "top_provider": { "context_length": 128000, @@ -11559,12 +11751,13 @@ "structured_outputs", "web_search_options" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "google/gemma-3-27b-it:free", "canonical_slug": "google/gemma-3-27b-it", - "hugging_face_id": "", + "hugging_face_id": "google/gemma-3-27b-it", "name": "Google: Gemma 3 27B (free)", "created": 1741756359, "description": "Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities, including structured outputs and function calling. Gemma 3 27B is Google's latest open source model, successor to [Gemma 2](google/gemma-2-27b-it)", @@ -11583,11 +11776,7 @@ }, "pricing": { "prompt": "0", - "completion": "0", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0" }, "top_provider": { "context_length": 131072, @@ -11603,18 +11792,22 @@ "response_format", "seed", "stop", - "structured_outputs", "temperature", "tool_choice", "tools", "top_p" ], - "default_parameters": {} + "default_parameters": { + "temperature": null, + "top_p": null, + "frequency_penalty": null + }, + "expiration_date": null }, { "id": "google/gemma-3-27b-it", "canonical_slug": "google/gemma-3-27b-it", - "hugging_face_id": "", + "hugging_face_id": "google/gemma-3-27b-it", "name": "Google: Gemma 3 27B", "created": 1741756359, "description": "Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities, including structured outputs and function calling. Gemma 3 27B is Google's latest open source model, successor to [Gemma 2](google/gemma-2-27b-it)", @@ -11662,7 +11855,12 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": { + "temperature": null, + "top_p": null, + "frequency_penalty": null + }, + "expiration_date": null }, { "id": "thedrummer/skyfall-36b-v2", @@ -11701,7 +11899,6 @@ "frequency_penalty", "logit_bias", "max_tokens", - "min_p", "presence_penalty", "repetition_penalty", "seed", @@ -11710,56 +11907,8 @@ "top_k", "top_p" ], - "default_parameters": {} - }, - { - "id": "microsoft/phi-4-multimodal-instruct", - "canonical_slug": "microsoft/phi-4-multimodal-instruct", - "hugging_face_id": "microsoft/Phi-4-multimodal-instruct", - "name": "Microsoft: Phi 4 Multimodal Instruct", - "created": 1741396284, - "description": "Phi-4 Multimodal Instruct is a versatile 5.6B parameter foundation model that combines advanced reasoning and instruction-following capabilities across both text and visual inputs, providing accurate text outputs. The unified architecture enables efficient, low-latency inference, suitable for edge and mobile deployments. Phi-4 Multimodal Instruct supports text inputs in multiple languages including Arabic, Chinese, English, French, German, Japanese, Spanish, and more, with visual input optimized primarily for English. It delivers impressive performance on multimodal tasks involving mathematical, scientific, and document reasoning, providing developers and enterprises a powerful yet compact model for sophisticated interactive applications. For more information, see the [Phi-4 Multimodal blog post](https://azure.microsoft.com/en-us/blog/empowering-innovation-the-next-generation-of-the-phi-family/).\n", - "context_length": 131072, - "architecture": { - "modality": "text+image->text", - "input_modalities": [ - "text", - "image" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Other", - "instruct_type": null - }, - "pricing": { - "prompt": "0.00000005", - "completion": "0.0000001", - "request": "0", - "image": "0.00017685", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 131072, - "max_completion_tokens": null, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "frequency_penalty", - "max_tokens", - "min_p", - "presence_penalty", - "repetition_penalty", - "response_format", - "seed", - "stop", - "temperature", - "top_k", - "top_p" - ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "perplexity/sonar-reasoning-pro", @@ -11806,7 +11955,8 @@ "top_p", "web_search_options" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "perplexity/sonar-pro", @@ -11851,7 +12001,8 @@ "top_p", "web_search_options" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "perplexity/sonar-deep-research", @@ -11897,7 +12048,8 @@ "top_p", "web_search_options" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "qwen/qwq-32b", @@ -11920,11 +12072,7 @@ }, "pricing": { "prompt": "0.00000015", - "completion": "0.0000004", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.0000004" }, "top_provider": { "context_length": 32768, @@ -11951,7 +12099,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "google/gemini-2.0-flash-lite-001", @@ -11962,7 +12111,7 @@ "description": "Gemini 2.0 Flash Lite offers a significantly faster time to first token (TTFT) compared to [Gemini Flash 1.5](/google/gemini-flash-1.5), while maintaining quality on par with larger models like [Gemini Pro 1.5](/google/gemini-pro-1.5), all at extremely economical token prices.", "context_length": 1048576, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file+audio+video->text", "input_modalities": [ "text", "image", @@ -11979,10 +12128,9 @@ "pricing": { "prompt": "0.000000075", "completion": "0.0000003", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "image": "0.000000075", + "audio": "0.000000075", + "internal_reasoning": "0.0000003" }, "top_provider": { "context_length": 1048576, @@ -12005,7 +12153,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": "2026-03-03" }, { "id": "anthropic/claude-3.7-sonnet:thinking", @@ -12016,7 +12165,7 @@ "description": "Claude 3.7 Sonnet is an advanced large language model with improved reasoning, coding, and problem-solving capabilities. It introduces a hybrid reasoning approach, allowing users to choose between rapid responses and extended, step-by-step processing for complex tasks. The model demonstrates notable improvements in coding, particularly in front-end development and full-stack updates, and excels in agentic workflows, where it can autonomously navigate multi-step processes. \n\nClaude 3.7 Sonnet maintains performance parity with its predecessor in standard mode while offering an extended reasoning mode for enhanced accuracy in math, coding, and instruction-following tasks.\n\nRead more at the [blog post here](https://www.anthropic.com/news/claude-3-7-sonnet)", "context_length": 200000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "text", "image", @@ -12058,7 +12207,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "anthropic/claude-3.7-sonnet", @@ -12069,7 +12219,7 @@ "description": "Claude 3.7 Sonnet is an advanced large language model with improved reasoning, coding, and problem-solving capabilities. It introduces a hybrid reasoning approach, allowing users to choose between rapid responses and extended, step-by-step processing for complex tasks. The model demonstrates notable improvements in coding, particularly in front-end development and full-stack updates, and excels in agentic workflows, where it can autonomously navigate multi-step processes. \n\nClaude 3.7 Sonnet maintains performance parity with its predecessor in standard mode while offering an extended reasoning mode for enhanced accuracy in math, coding, and instruction-following tasks.\n\nRead more at the [blog post here](https://www.anthropic.com/news/claude-3-7-sonnet)", "context_length": 200000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "text", "image", @@ -12112,7 +12262,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "mistralai/mistral-saba", @@ -12135,11 +12286,7 @@ }, "pricing": { "prompt": "0.0000002", - "completion": "0.0000006", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.0000006" }, "top_provider": { "context_length": 32768, @@ -12162,7 +12309,8 @@ ], "default_parameters": { "temperature": 0.3 - } + }, + "expiration_date": null }, { "id": "meta-llama/llama-guard-3-8b", @@ -12200,17 +12348,15 @@ "supported_parameters": [ "frequency_penalty", "max_tokens", - "min_p", "presence_penalty", "repetition_penalty", - "response_format", "seed", - "stop", "temperature", "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "openai/o3-mini-high", @@ -12221,7 +12367,7 @@ "description": "OpenAI o3-mini-high is the same model as [o3-mini](/openai/o3-mini) with reasoning_effort set to high. \n\no3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and coding. The model features three adjustable reasoning effort levels and supports key developer capabilities including function calling, structured outputs, and streaming, though it does not include vision processing capabilities.\n\nThe model demonstrates significant improvements over its predecessor, with expert testers preferring its responses 56% of the time and noting a 39% reduction in major errors on complex questions. With medium reasoning effort settings, o3-mini matches the performance of the larger o1 model on challenging reasoning evaluations like AIME and GPQA, while maintaining lower latency and cost.", "context_length": 200000, "architecture": { - "modality": "text->text", + "modality": "text+file->text", "input_modalities": [ "text", "file" @@ -12235,10 +12381,6 @@ "pricing": { "prompt": "0.0000011", "completion": "0.0000044", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0", "input_cache_read": "0.00000055" }, "top_provider": { @@ -12255,7 +12397,12 @@ "tool_choice", "tools" ], - "default_parameters": {} + "default_parameters": { + "temperature": null, + "top_p": null, + "frequency_penalty": null + }, + "expiration_date": null }, { "id": "google/gemini-2.0-flash-001", @@ -12266,7 +12413,7 @@ "description": "Gemini Flash 2.0 offers a significantly faster time to first token (TTFT) compared to [Gemini Flash 1.5](/google/gemini-flash-1.5), while maintaining quality on par with larger models like [Gemini Pro 1.5](/google/gemini-pro-1.5). It introduces notable enhancements in multimodal understanding, coding capabilities, complex instruction following, and function calling. These advancements come together to deliver more seamless and robust agentic experiences.", "context_length": 1048576, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file+audio+video->text", "input_modalities": [ "text", "image", @@ -12283,13 +12430,11 @@ "pricing": { "prompt": "0.0000001", "completion": "0.0000004", - "request": "0", - "image": "0.0000258", + "image": "0.0000001", "audio": "0.0000007", - "web_search": "0", - "internal_reasoning": "0", + "internal_reasoning": "0.0000004", "input_cache_read": "0.000000025", - "input_cache_write": "0.0000001833" + "input_cache_write": "0.00000008333333333333334" }, "top_provider": { "context_length": 1048576, @@ -12312,7 +12457,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": "2026-03-31" }, { "id": "qwen/qwen-vl-plus", @@ -12356,7 +12502,8 @@ "temperature", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "aion-labs/aion-1.0", @@ -12379,11 +12526,7 @@ }, "pricing": { "prompt": "0.000004", - "completion": "0.000008", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.000008" }, "top_provider": { "context_length": 131072, @@ -12398,7 +12541,8 @@ "temperature", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "aion-labs/aion-1.0-mini", @@ -12421,11 +12565,7 @@ }, "pricing": { "prompt": "0.0000007", - "completion": "0.0000014", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.0000014" }, "top_provider": { "context_length": 131072, @@ -12440,7 +12580,8 @@ "temperature", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "aion-labs/aion-rp-llama-3.1-8b", @@ -12463,11 +12604,7 @@ }, "pricing": { "prompt": "0.0000008", - "completion": "0.0000016", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.0000016" }, "top_provider": { "context_length": 32768, @@ -12480,7 +12617,8 @@ "temperature", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "qwen/qwen-vl-max", @@ -12530,7 +12668,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "qwen/qwen-turbo", @@ -12576,7 +12715,8 @@ "tools", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "qwen/qwen2.5-vl-72b-instruct", @@ -12599,8 +12739,8 @@ "instruct_type": null }, "pricing": { - "prompt": "0.00000007", - "completion": "0.00000026", + "prompt": "0.00000015", + "completion": "0.0000006", "request": "0", "image": "0", "web_search": "0", @@ -12627,7 +12767,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "qwen/qwen-plus", @@ -12673,7 +12814,8 @@ "tools", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "qwen/qwen-max", @@ -12719,7 +12861,8 @@ "tools", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "openai/o3-mini", @@ -12730,7 +12873,7 @@ "description": "OpenAI o3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and coding.\n\nThis model supports the `reasoning_effort` parameter, which can be set to \"high\", \"medium\", or \"low\" to control the thinking time of the model. The default is \"medium\". OpenRouter also offers the model slug `openai/o3-mini-high` to default the parameter to \"high\".\n\nThe model features three adjustable reasoning effort levels and supports key developer capabilities including function calling, structured outputs, and streaming, though it does not include vision processing capabilities.\n\nThe model demonstrates significant improvements over its predecessor, with expert testers preferring its responses 56% of the time and noting a 39% reduction in major errors on complex questions. With medium reasoning effort settings, o3-mini matches the performance of the larger o1 model on challenging reasoning evaluations like AIME and GPQA, while maintaining lower latency and cost.", "context_length": 200000, "architecture": { - "modality": "text->text", + "modality": "text+file->text", "input_modalities": [ "text", "file" @@ -12744,10 +12887,6 @@ "pricing": { "prompt": "0.0000011", "completion": "0.0000044", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0", "input_cache_read": "0.00000055" }, "top_provider": { @@ -12764,7 +12903,8 @@ "tool_choice", "tools" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "mistralai/mistral-small-24b-instruct-2501", @@ -12820,7 +12960,8 @@ "temperature": 0.3, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "deepseek/deepseek-r1-distill-qwen-32b", @@ -12829,57 +12970,6 @@ "name": "DeepSeek: R1 Distill Qwen 32B", "created": 1738194830, "description": "DeepSeek R1 Distill Qwen 32B is a distilled large language model based on [Qwen 2.5 32B](https://huggingface.co/Qwen/Qwen2.5-32B), using outputs from [DeepSeek R1](/deepseek/deepseek-r1). It outperforms OpenAI's o1-mini across various benchmarks, achieving new state-of-the-art results for dense models.\\n\\nOther benchmark results include:\\n\\n- AIME 2024 pass@1: 72.6\\n- MATH-500 pass@1: 94.3\\n- CodeForces Rating: 1691\\n\\nThe model leverages fine-tuning from DeepSeek R1's outputs, enabling competitive performance comparable to larger frontier models.", - "context_length": 64000, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Qwen", - "instruct_type": "deepseek-r1" - }, - "pricing": { - "prompt": "0.00000024", - "completion": "0.00000024", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 64000, - "max_completion_tokens": 32000, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "frequency_penalty", - "include_reasoning", - "max_tokens", - "min_p", - "presence_penalty", - "reasoning", - "repetition_penalty", - "response_format", - "seed", - "stop", - "structured_outputs", - "temperature", - "top_k", - "top_p" - ], - "default_parameters": {} - }, - { - "id": "deepseek/deepseek-r1-distill-qwen-14b", - "canonical_slug": "deepseek/deepseek-r1-distill-qwen-14b", - "hugging_face_id": "deepseek-ai/DeepSeek-R1-Distill-Qwen-14B", - "name": "DeepSeek: R1 Distill Qwen 14B", - "created": 1738193940, - "description": "DeepSeek R1 Distill Qwen 14B is a distilled large language model based on [Qwen 2.5 14B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-14B), using outputs from [DeepSeek R1](/deepseek/deepseek-r1). It outperforms OpenAI's o1-mini across various benchmarks, achieving new state-of-the-art results for dense models.\n\nOther benchmark results include:\n\n- AIME 2024 pass@1: 69.7\n- MATH-500 pass@1: 93.9\n- CodeForces Rating: 1481\n\nThe model leverages fine-tuning from DeepSeek R1's outputs, enabling competitive performance comparable to larger frontier models.", "context_length": 32768, "architecture": { "modality": "text->text", @@ -12893,16 +12983,12 @@ "instruct_type": "deepseek-r1" }, "pricing": { - "prompt": "0.00000012", - "completion": "0.00000012", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "prompt": "0.00000029", + "completion": "0.00000029" }, "top_provider": { "context_length": 32768, - "max_completion_tokens": 16384, + "max_completion_tokens": null, "is_moderated": false }, "per_request_limits": null, @@ -12921,53 +13007,8 @@ "top_k", "top_p" ], - "default_parameters": {} - }, - { - "id": "perplexity/sonar-reasoning", - "canonical_slug": "perplexity/sonar-reasoning", - "hugging_face_id": "", - "name": "Perplexity: Sonar Reasoning", - "created": 1738131107, - "description": "Sonar Reasoning is a reasoning model provided by Perplexity based on [DeepSeek R1](/deepseek/deepseek-r1).\n\nIt allows developers to utilize long chain of thought with built-in web search. Sonar Reasoning is uncensored and hosted in US datacenters. ", - "context_length": 127000, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Other", - "instruct_type": "deepseek-r1" - }, - "pricing": { - "prompt": "0.000001", - "completion": "0.000005", - "request": "0.005", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 127000, - "max_completion_tokens": null, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "frequency_penalty", - "include_reasoning", - "max_tokens", - "presence_penalty", - "reasoning", - "temperature", - "top_k", - "top_p", - "web_search_options" - ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "perplexity/sonar", @@ -13012,7 +13053,8 @@ "top_p", "web_search_options" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "deepseek/deepseek-r1-distill-llama-70b", @@ -13066,7 +13108,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "deepseek/deepseek-r1", @@ -13075,7 +13118,7 @@ "name": "DeepSeek: R1", "created": 1737381095, "description": "DeepSeek R1 is here: Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inference pass.\n\nFully open-source model & [technical report](https://api-docs.deepseek.com/news/news250120).\n\nMIT licensed: Distill & commercialize freely!", - "context_length": 163840, + "context_length": 64000, "architecture": { "modality": "text->text", "input_modalities": [ @@ -13088,16 +13131,16 @@ "instruct_type": "deepseek-r1" }, "pricing": { - "prompt": "0.0000003", - "completion": "0.0000012", + "prompt": "0.0000007", + "completion": "0.0000025", "request": "0", "image": "0", "web_search": "0", "internal_reasoning": "0" }, "top_provider": { - "context_length": 163840, - "max_completion_tokens": null, + "context_length": 64000, + "max_completion_tokens": 16000, "is_moderated": false }, "per_request_limits": null, @@ -13105,21 +13148,19 @@ "frequency_penalty", "include_reasoning", "max_tokens", - "min_p", "presence_penalty", "reasoning", "repetition_penalty", - "response_format", "seed", "stop", - "structured_outputs", "temperature", "tool_choice", "tools", "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "minimax/minimax-01", @@ -13160,7 +13201,8 @@ "temperature", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "microsoft/phi-4", @@ -13183,11 +13225,7 @@ }, "pricing": { "prompt": "0.00000006", - "completion": "0.00000014", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.00000014" }, "top_provider": { "context_length": 16384, @@ -13209,7 +13247,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "sao10k/l3.1-70b-hanami-x1", @@ -13257,7 +13296,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "deepseek/deepseek-chat", @@ -13308,7 +13348,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "sao10k/l3.3-euryale-70b", @@ -13331,11 +13372,7 @@ }, "pricing": { "prompt": "0.00000065", - "completion": "0.00000075", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.00000075" }, "top_provider": { "context_length": 131072, @@ -13357,7 +13394,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "openai/o1", @@ -13368,7 +13406,7 @@ "description": "The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding. The o1 model series is trained with large-scale reinforcement learning to reason using chain of thought. \n\nThe o1 models are optimized for math, science, programming, and other STEM-related tasks. They consistently exhibit PhD-level accuracy on benchmarks in physics, chemistry, and biology. Learn more in the [launch announcement](https://openai.com/o1).\n", "context_length": 200000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "text", "image", @@ -13383,10 +13421,6 @@ "pricing": { "prompt": "0.000015", "completion": "0.00006", - "request": "0", - "image": "0.021675", - "web_search": "0", - "internal_reasoning": "0", "input_cache_read": "0.0000075" }, "top_provider": { @@ -13403,7 +13437,8 @@ "tool_choice", "tools" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "cohere/command-r7b-12-2024", @@ -13450,7 +13485,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "google/gemini-2.0-flash-exp:free", @@ -13474,11 +13510,7 @@ }, "pricing": { "prompt": "0", - "completion": "0", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0" }, "top_provider": { "context_length": 1048576, @@ -13496,7 +13528,8 @@ "tools", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": "2026-03-03" }, { "id": "meta-llama/llama-3.3-70b-instruct:free", @@ -13519,11 +13552,7 @@ }, "pricing": { "prompt": "0", - "completion": "0", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0" }, "top_provider": { "context_length": 131072, @@ -13544,7 +13573,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "meta-llama/llama-3.3-70b-instruct", @@ -13598,7 +13628,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "amazon/nova-lite-v1", @@ -13642,7 +13673,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "amazon/nova-micro-v1", @@ -13685,7 +13717,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "amazon/nova-pro-v1", @@ -13729,7 +13762,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "openai/gpt-4o-2024-11-20", @@ -13740,7 +13774,7 @@ "description": "The 2024-11-20 version of GPT-4o offers a leveled-up creative writing ability with more natural, engaging, and tailored writing to improve relevance & readability. It’s also better at working with uploaded files, providing deeper insights & more thorough responses.\n\nGPT-4o (\"o\" for \"omni\") is OpenAI's latest AI model, supporting both text and image inputs with text outputs. It maintains the intelligence level of [GPT-4 Turbo](/models/openai/gpt-4-turbo) while being twice as fast and 50% more cost-effective. GPT-4o also offers improved performance in processing non-English languages and enhanced visual capabilities.", "context_length": 128000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "text", "image", @@ -13755,10 +13789,6 @@ "pricing": { "prompt": "0.0000025", "completion": "0.00001", - "request": "0", - "image": "0.003613", - "web_search": "0", - "internal_reasoning": "0", "input_cache_read": "0.00000125" }, "top_provider": { @@ -13784,7 +13814,8 @@ "top_p", "web_search_options" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "mistralai/mistral-large-2411", @@ -13807,11 +13838,7 @@ }, "pricing": { "prompt": "0.000002", - "completion": "0.000006", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.000006" }, "top_provider": { "context_length": 131072, @@ -13834,7 +13861,8 @@ ], "default_parameters": { "temperature": 0.3 - } + }, + "expiration_date": null }, { "id": "mistralai/mistral-large-2407", @@ -13857,11 +13885,7 @@ }, "pricing": { "prompt": "0.000002", - "completion": "0.000006", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.000006" }, "top_provider": { "context_length": 131072, @@ -13884,7 +13908,8 @@ ], "default_parameters": { "temperature": 0.3 - } + }, + "expiration_date": null }, { "id": "mistralai/pixtral-large-2411", @@ -13908,11 +13933,7 @@ }, "pricing": { "prompt": "0.000002", - "completion": "0.000006", - "request": "0", - "image": "0.002888", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.000006" }, "top_provider": { "context_length": 131072, @@ -13935,7 +13956,8 @@ ], "default_parameters": { "temperature": 0.3 - } + }, + "expiration_date": null }, { "id": "qwen/qwen-2.5-coder-32b-instruct", @@ -13985,7 +14007,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "raifle/sorcererlm-8x22b", @@ -14033,7 +14056,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "thedrummer/unslopnemo-12b", @@ -14056,11 +14080,7 @@ }, "pricing": { "prompt": "0.0000004", - "completion": "0.0000004", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.0000004" }, "top_provider": { "context_length": 32768, @@ -14080,55 +14100,8 @@ "tools", "top_p" ], - "default_parameters": {} - }, - { - "id": "anthropic/claude-3.5-haiku-20241022", - "canonical_slug": "anthropic/claude-3-5-haiku-20241022", - "hugging_face_id": null, - "name": "Anthropic: Claude 3.5 Haiku (2024-10-22)", - "created": 1730678400, - "description": "Claude 3.5 Haiku features enhancements across all skill sets including coding, tool use, and reasoning. As the fastest model in the Anthropic lineup, it offers rapid response times suitable for applications that require high interactivity and low latency, such as user-facing chatbots and on-the-fly code completions. It also excels in specialized tasks like data extraction and real-time content moderation, making it a versatile tool for a broad range of industries.\n\nIt does not support image inputs.\n\nSee the launch announcement and benchmark results [here](https://www.anthropic.com/news/3-5-models-and-computer-use)", - "context_length": 200000, - "architecture": { - "modality": "text+image->text", - "input_modalities": [ - "text", - "image", - "file" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Claude", - "instruct_type": null - }, - "pricing": { - "prompt": "0.0000008", - "completion": "0.000004", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0", - "input_cache_read": "0.00000008", - "input_cache_write": "0.000001" - }, - "top_provider": { - "context_length": 200000, - "max_completion_tokens": 8192, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "max_tokens", - "stop", - "temperature", - "tool_choice", - "tools", - "top_k", - "top_p" - ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "anthropic/claude-3.5-haiku", @@ -14179,7 +14152,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "anthracite-org/magnum-v4-72b", @@ -14231,7 +14205,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "anthropic/claude-3.5-sonnet", @@ -14242,7 +14217,7 @@ "description": "New Claude 3.5 Sonnet delivers better-than-Opus capabilities, faster-than-Sonnet speeds, at the same Sonnet prices. Sonnet is particularly good at:\n\n- Coding: Scores ~49% on SWE-Bench Verified, higher than the last best score, and without any fancy prompt scaffolding\n- Data science: Augments human data science expertise; navigates unstructured data while using multiple tools for insights\n- Visual processing: excelling at interpreting charts, graphs, and images, accurately transcribing text to derive insights beyond just the text alone\n- Agentic tasks: exceptional tool use, making it great at agentic tasks (i.e. complex, multi-step problem solving tasks that require engaging with other systems)\n\n#multimodal", "context_length": 200000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "text", "image", @@ -14277,57 +14252,8 @@ "top_k", "top_p" ], - "default_parameters": {} - }, - { - "id": "mistralai/ministral-8b", - "canonical_slug": "mistralai/ministral-8b", - "hugging_face_id": null, - "name": "Mistral: Ministral 8B", - "created": 1729123200, - "description": "Ministral 8B is an 8B parameter model featuring a unique interleaved sliding-window attention pattern for faster, memory-efficient inference. Designed for edge use cases, it supports up to 128k context length and excels in knowledge and reasoning tasks. It outperforms peers in the sub-10B category, making it perfect for low-latency, privacy-first applications.", - "context_length": 131072, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Mistral", - "instruct_type": null - }, - "pricing": { - "prompt": "0.0000001", - "completion": "0.0000001", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 131072, - "max_completion_tokens": null, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "frequency_penalty", - "max_tokens", - "presence_penalty", - "response_format", - "seed", - "stop", - "structured_outputs", - "temperature", - "tool_choice", - "tools", - "top_p" - ], - "default_parameters": { - "temperature": 0.3 - } + "default_parameters": {}, + "expiration_date": null }, { "id": "mistralai/ministral-3b", @@ -14350,11 +14276,7 @@ }, "pricing": { "prompt": "0.00000004", - "completion": "0.00000004", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.00000004" }, "top_provider": { "context_length": 131072, @@ -14377,7 +14299,55 @@ ], "default_parameters": { "temperature": 0.3 - } + }, + "expiration_date": null + }, + { + "id": "mistralai/ministral-8b", + "canonical_slug": "mistralai/ministral-8b", + "hugging_face_id": null, + "name": "Mistral: Ministral 8B", + "created": 1729123200, + "description": "Ministral 8B is an 8B parameter model featuring a unique interleaved sliding-window attention pattern for faster, memory-efficient inference. Designed for edge use cases, it supports up to 128k context length and excels in knowledge and reasoning tasks. It outperforms peers in the sub-10B category, making it perfect for low-latency, privacy-first applications.", + "context_length": 131072, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Mistral", + "instruct_type": null + }, + "pricing": { + "prompt": "0.0000001", + "completion": "0.0000001" + }, + "top_provider": { + "context_length": 131072, + "max_completion_tokens": null, + "is_moderated": false + }, + "per_request_limits": null, + "supported_parameters": [ + "frequency_penalty", + "max_tokens", + "presence_penalty", + "response_format", + "seed", + "stop", + "structured_outputs", + "temperature", + "tool_choice", + "tools", + "top_p" + ], + "default_parameters": { + "temperature": 0.3 + }, + "expiration_date": null }, { "id": "qwen/qwen-2.5-7b-instruct", @@ -14422,6 +14392,8 @@ "seed", "stop", "temperature", + "tool_choice", + "tools", "top_k", "top_p" ], @@ -14429,7 +14401,8 @@ "temperature": null, "top_p": null, "frequency_penalty": null - } + }, + "expiration_date": null }, { "id": "nvidia/llama-3.1-nemotron-70b-instruct", @@ -14479,7 +14452,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "inflection/inflection-3-pi", @@ -14520,7 +14494,8 @@ "temperature", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "inflection/inflection-3-productivity", @@ -14561,7 +14536,8 @@ "temperature", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "thedrummer/rocinante-12b", @@ -14584,11 +14560,7 @@ }, "pricing": { "prompt": "0.00000017", - "completion": "0.00000043", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.00000043" }, "top_provider": { "context_length": 32768, @@ -14613,7 +14585,54 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null + }, + { + "id": "meta-llama/llama-3.2-1b-instruct", + "canonical_slug": "meta-llama/llama-3.2-1b-instruct", + "hugging_face_id": "meta-llama/Llama-3.2-1B-Instruct", + "name": "Meta: Llama 3.2 1B Instruct", + "created": 1727222400, + "description": "Llama 3.2 1B is a 1-billion-parameter language model focused on efficiently performing natural language tasks, such as summarization, dialogue, and multilingual text analysis. Its smaller size allows it to operate efficiently in low-resource environments while maintaining strong task performance.\n\nSupporting eight core languages and fine-tunable for more, Llama 1.3B is ideal for businesses or developers seeking lightweight yet powerful AI solutions that can operate in diverse multilingual settings without the high computational demand of larger models.\n\nClick here for the [original model card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/MODEL_CARD.md).\n\nUsage of this model is subject to [Meta's Acceptable Use Policy](https://www.llama.com/llama3/use-policy/).", + "context_length": 60000, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Llama3", + "instruct_type": "llama3" + }, + "pricing": { + "prompt": "0.000000027", + "completion": "0.0000002", + "request": "0", + "image": "0", + "web_search": "0", + "internal_reasoning": "0" + }, + "top_provider": { + "context_length": 60000, + "max_completion_tokens": null, + "is_moderated": false + }, + "per_request_limits": null, + "supported_parameters": [ + "frequency_penalty", + "max_tokens", + "presence_penalty", + "repetition_penalty", + "seed", + "temperature", + "top_k", + "top_p" + ], + "default_parameters": {}, + "expiration_date": null }, { "id": "meta-llama/llama-3.2-3b-instruct:free", @@ -14657,7 +14676,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "meta-llama/llama-3.2-3b-instruct", @@ -14703,106 +14723,11 @@ "seed", "stop", "temperature", - "tool_choice", - "tools", "top_k", "top_p" ], - "default_parameters": {} - }, - { - "id": "meta-llama/llama-3.2-1b-instruct", - "canonical_slug": "meta-llama/llama-3.2-1b-instruct", - "hugging_face_id": "meta-llama/Llama-3.2-1B-Instruct", - "name": "Meta: Llama 3.2 1B Instruct", - "created": 1727222400, - "description": "Llama 3.2 1B is a 1-billion-parameter language model focused on efficiently performing natural language tasks, such as summarization, dialogue, and multilingual text analysis. Its smaller size allows it to operate efficiently in low-resource environments while maintaining strong task performance.\n\nSupporting eight core languages and fine-tunable for more, Llama 1.3B is ideal for businesses or developers seeking lightweight yet powerful AI solutions that can operate in diverse multilingual settings without the high computational demand of larger models.\n\nClick here for the [original model card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/MODEL_CARD.md).\n\nUsage of this model is subject to [Meta's Acceptable Use Policy](https://www.llama.com/llama3/use-policy/).", - "context_length": 60000, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Llama3", - "instruct_type": "llama3" - }, - "pricing": { - "prompt": "0.000000027", - "completion": "0.0000002", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 60000, - "max_completion_tokens": null, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "frequency_penalty", - "max_tokens", - "presence_penalty", - "repetition_penalty", - "seed", - "temperature", - "top_k", - "top_p" - ], - "default_parameters": {} - }, - { - "id": "meta-llama/llama-3.2-90b-vision-instruct", - "canonical_slug": "meta-llama/llama-3.2-90b-vision-instruct", - "hugging_face_id": "meta-llama/Llama-3.2-90B-Vision-Instruct", - "name": "Meta: Llama 3.2 90B Vision Instruct", - "created": 1727222400, - "description": "The Llama 90B Vision model is a top-tier, 90-billion-parameter multimodal model designed for the most challenging visual reasoning and language tasks. It offers unparalleled accuracy in image captioning, visual question answering, and advanced image-text comprehension. Pre-trained on vast multimodal datasets and fine-tuned with human feedback, the Llama 90B Vision is engineered to handle the most demanding image-based AI tasks.\n\nThis model is perfect for industries requiring cutting-edge multimodal AI capabilities, particularly those dealing with complex, real-time visual and textual analysis.\n\nClick here for the [original model card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/MODEL_CARD_VISION.md).\n\nUsage of this model is subject to [Meta's Acceptable Use Policy](https://www.llama.com/llama3/use-policy/).", - "context_length": 32768, - "architecture": { - "modality": "text+image->text", - "input_modalities": [ - "text", - "image" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Llama3", - "instruct_type": "llama3" - }, - "pricing": { - "prompt": "0.00000035", - "completion": "0.0000004", - "request": "0", - "image": "0.0005058", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 32768, - "max_completion_tokens": 16384, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "frequency_penalty", - "max_tokens", - "min_p", - "presence_penalty", - "repetition_penalty", - "response_format", - "seed", - "stop", - "temperature", - "top_k", - "top_p" - ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "meta-llama/llama-3.2-11b-vision-instruct", @@ -14852,7 +14777,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "qwen/qwen-2.5-72b-instruct", @@ -14904,7 +14830,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "neversleep/llama-3.1-lumimaid-8b", @@ -14927,11 +14854,7 @@ }, "pricing": { "prompt": "0.00000009", - "completion": "0.0000006", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.0000006" }, "top_provider": { "context_length": 32768, @@ -14949,7 +14872,8 @@ "temperature", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "mistralai/pixtral-12b", @@ -15004,56 +14928,8 @@ ], "default_parameters": { "temperature": 0.3 - } - }, - { - "id": "cohere/command-r-08-2024", - "canonical_slug": "cohere/command-r-08-2024", - "hugging_face_id": null, - "name": "Cohere: Command R (08-2024)", - "created": 1724976000, - "description": "command-r-08-2024 is an update of the [Command R](/models/cohere/command-r) with improved performance for multilingual retrieval-augmented generation (RAG) and tool use. More broadly, it is better at math, code and reasoning and is competitive with the previous version of the larger Command R+ model.\n\nRead the launch post [here](https://docs.cohere.com/changelog/command-gets-refreshed).\n\nUse of this model is subject to Cohere's [Usage Policy](https://docs.cohere.com/docs/usage-policy) and [SaaS Agreement](https://cohere.com/saas-agreement).", - "context_length": 128000, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Cohere", - "instruct_type": null }, - "pricing": { - "prompt": "0.00000015", - "completion": "0.0000006", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 128000, - "max_completion_tokens": 4000, - "is_moderated": true - }, - "per_request_limits": null, - "supported_parameters": [ - "frequency_penalty", - "max_tokens", - "presence_penalty", - "response_format", - "seed", - "stop", - "structured_outputs", - "temperature", - "tool_choice", - "tools", - "top_k", - "top_p" - ], - "default_parameters": {} + "expiration_date": null }, { "id": "cohere/command-r-plus-08-2024", @@ -15102,16 +14978,17 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { - "id": "sao10k/l3.1-euryale-70b", - "canonical_slug": "sao10k/l3.1-euryale-70b", - "hugging_face_id": "Sao10K/L3.1-70B-Euryale-v2.2", - "name": "Sao10K: Llama 3.1 Euryale 70B v2.2", - "created": 1724803200, - "description": "Euryale L3.1 70B v2.2 is a model focused on creative roleplay from [Sao10k](https://ko-fi.com/sao10k). It is the successor of [Euryale L3 70B v2.1](/models/sao10k/l3-euryale-70b).", - "context_length": 32768, + "id": "cohere/command-r-08-2024", + "canonical_slug": "cohere/command-r-08-2024", + "hugging_face_id": null, + "name": "Cohere: Command R (08-2024)", + "created": 1724976000, + "description": "command-r-08-2024 is an update of the [Command R](/models/cohere/command-r) with improved performance for multilingual retrieval-augmented generation (RAG) and tool use. More broadly, it is better at math, code and reasoning and is competitive with the previous version of the larger Command R+ model.\n\nRead the launch post [here](https://docs.cohere.com/changelog/command-gets-refreshed).\n\nUse of this model is subject to Cohere's [Usage Policy](https://docs.cohere.com/docs/usage-policy) and [SaaS Agreement](https://cohere.com/saas-agreement).", + "context_length": 128000, "architecture": { "modality": "text->text", "input_modalities": [ @@ -15120,29 +14997,27 @@ "output_modalities": [ "text" ], - "tokenizer": "Llama3", - "instruct_type": "llama3" + "tokenizer": "Cohere", + "instruct_type": null }, "pricing": { - "prompt": "0.00000065", - "completion": "0.00000075", + "prompt": "0.00000015", + "completion": "0.0000006", "request": "0", "image": "0", "web_search": "0", "internal_reasoning": "0" }, "top_provider": { - "context_length": 32768, - "max_completion_tokens": null, - "is_moderated": false + "context_length": 128000, + "max_completion_tokens": 4000, + "is_moderated": true }, "per_request_limits": null, "supported_parameters": [ "frequency_penalty", "max_tokens", - "min_p", "presence_penalty", - "repetition_penalty", "response_format", "seed", "stop", @@ -15153,7 +15028,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "qwen/qwen-2.5-vl-7b-instruct:free", @@ -15177,11 +15053,7 @@ }, "pricing": { "prompt": "0", - "completion": "0", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0" }, "top_provider": { "context_length": 32768, @@ -15196,7 +15068,8 @@ "repetition_penalty", "temperature" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "qwen/qwen-2.5-vl-7b-instruct", @@ -15245,16 +15118,17 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { - "id": "microsoft/phi-3.5-mini-128k-instruct", - "canonical_slug": "microsoft/phi-3.5-mini-128k-instruct", - "hugging_face_id": "microsoft/Phi-3.5-mini-instruct", - "name": "Microsoft: Phi-3.5 Mini 128K Instruct", - "created": 1724198400, - "description": "Phi-3.5 models are lightweight, state-of-the-art open models. These models were trained with Phi-3 datasets that include both synthetic data and the filtered, publicly available websites data, with a focus on high quality and reasoning-dense properties. Phi-3.5 Mini uses 3.8B parameters, and is a dense decoder-only transformer model using the same tokenizer as [Phi-3 Mini](/models/microsoft/phi-3-mini-128k-instruct).\n\nThe models underwent a rigorous enhancement process, incorporating both supervised fine-tuning, proximal policy optimization, and direct preference optimization to ensure precise instruction adherence and robust safety measures. When assessed against benchmarks that test common sense, language understanding, math, code, long context and logical reasoning, Phi-3.5 models showcased robust and state-of-the-art performance among models with less than 13 billion parameters.", - "context_length": 128000, + "id": "sao10k/l3.1-euryale-70b", + "canonical_slug": "sao10k/l3.1-euryale-70b", + "hugging_face_id": "Sao10K/L3.1-70B-Euryale-v2.2", + "name": "Sao10K: Llama 3.1 Euryale 70B v2.2", + "created": 1724803200, + "description": "Euryale L3.1 70B v2.2 is a model focused on creative roleplay from [Sao10k](https://ko-fi.com/sao10k). It is the successor of [Euryale L3 70B v2.1](/models/sao10k/l3-euryale-70b).", + "context_length": 32768, "architecture": { "modality": "text->text", "input_modalities": [ @@ -15263,31 +15137,37 @@ "output_modalities": [ "text" ], - "tokenizer": "Other", - "instruct_type": "phi3" + "tokenizer": "Llama3", + "instruct_type": "llama3" }, "pricing": { - "prompt": "0.0000001", - "completion": "0.0000001", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "prompt": "0.00000065", + "completion": "0.00000075" }, "top_provider": { - "context_length": 128000, + "context_length": 32768, "max_completion_tokens": null, "is_moderated": false }, "per_request_limits": null, "supported_parameters": [ + "frequency_penalty", "max_tokens", + "min_p", + "presence_penalty", + "repetition_penalty", + "response_format", + "seed", + "stop", + "structured_outputs", "temperature", "tool_choice", "tools", + "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "nousresearch/hermes-3-llama-3.1-70b", @@ -15310,11 +15190,7 @@ }, "pricing": { "prompt": "0.0000003", - "completion": "0.0000003", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.0000003" }, "top_provider": { "context_length": 65536, @@ -15336,7 +15212,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "nousresearch/hermes-3-llama-3.1-405b:free", @@ -15380,7 +15257,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "nousresearch/hermes-3-llama-3.1-405b", @@ -15428,7 +15306,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "openai/chatgpt-4o-latest", @@ -15452,11 +15331,7 @@ }, "pricing": { "prompt": "0.000005", - "completion": "0.000015", - "request": "0", - "image": "0.007225", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.000015" }, "top_provider": { "context_length": 128000, @@ -15478,7 +15353,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "sao10k/l3-lunaris-8b", @@ -15527,7 +15403,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "openai/gpt-4o-2024-08-06", @@ -15538,7 +15415,7 @@ "description": "The 2024-08-06 version of GPT-4o offers improved performance in structured outputs, with the ability to supply a JSON schema in the respone_format. Read more [here](https://openai.com/index/introducing-structured-outputs-in-the-api/).\n\nGPT-4o (\"o\" for \"omni\") is OpenAI's latest AI model, supporting both text and image inputs with text outputs. It maintains the intelligence level of [GPT-4 Turbo](/models/openai/gpt-4-turbo) while being twice as fast and 50% more cost-effective. GPT-4o also offers improved performance in processing non-English languages and enhanced visual capabilities.\n\nFor benchmarking against other models, it was briefly called [\"im-also-a-good-gpt2-chatbot\"](https://twitter.com/LiamFedus/status/1790064963966370209)", "context_length": 128000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "text", "image", @@ -15582,7 +15459,8 @@ "top_p", "web_search_options" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "meta-llama/llama-3.1-405b", @@ -15630,15 +15508,16 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { - "id": "meta-llama/llama-3.1-8b-instruct", - "canonical_slug": "meta-llama/llama-3.1-8b-instruct", - "hugging_face_id": "meta-llama/Meta-Llama-3.1-8B-Instruct", - "name": "Meta: Llama 3.1 8B Instruct", + "id": "meta-llama/llama-3.1-70b-instruct", + "canonical_slug": "meta-llama/llama-3.1-70b-instruct", + "hugging_face_id": "meta-llama/Meta-Llama-3.1-70B-Instruct", + "name": "Meta: Llama 3.1 70B Instruct", "created": 1721692800, - "description": "Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 8B instruct-tuned version is fast and efficient.\n\nIt has demonstrated strong performance compared to leading closed-source models in human evaluations.\n\nTo read more about the model release, [click here](https://ai.meta.com/blog/meta-llama-3-1/). Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).", + "description": "Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 70B instruct-tuned version is optimized for high quality dialogue usecases.\n\nIt has demonstrated strong performance compared to leading closed-source models in human evaluations.\n\nTo read more about the model release, [click here](https://ai.meta.com/blog/meta-llama-3-1/). Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).", "context_length": 131072, "architecture": { "modality": "text->text", @@ -15652,8 +15531,8 @@ "instruct_type": "llama3" }, "pricing": { - "prompt": "0.00000002", - "completion": "0.00000003", + "prompt": "0.0000004", + "completion": "0.0000004", "request": "0", "image": "0", "web_search": "0", @@ -15661,14 +15540,13 @@ }, "top_provider": { "context_length": 131072, - "max_completion_tokens": 16384, + "max_completion_tokens": null, "is_moderated": false }, "per_request_limits": null, "supported_parameters": [ "frequency_penalty", "logit_bias", - "logprobs", "max_tokens", "min_p", "presence_penalty", @@ -15676,15 +15554,14 @@ "response_format", "seed", "stop", - "structured_outputs", "temperature", "tool_choice", "tools", "top_k", - "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "meta-llama/llama-3.1-405b-instruct:free", @@ -15707,11 +15584,7 @@ }, "pricing": { "prompt": "0", - "completion": "0", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0" }, "top_provider": { "context_length": 131072, @@ -15726,7 +15599,8 @@ "repetition_penalty", "temperature" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "meta-llama/llama-3.1-405b-instruct", @@ -15778,16 +15652,17 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": "2026-02-06" }, { - "id": "meta-llama/llama-3.1-70b-instruct", - "canonical_slug": "meta-llama/llama-3.1-70b-instruct", - "hugging_face_id": "meta-llama/Meta-Llama-3.1-70B-Instruct", - "name": "Meta: Llama 3.1 70B Instruct", + "id": "meta-llama/llama-3.1-8b-instruct", + "canonical_slug": "meta-llama/llama-3.1-8b-instruct", + "hugging_face_id": "meta-llama/Meta-Llama-3.1-8B-Instruct", + "name": "Meta: Llama 3.1 8B Instruct", "created": 1721692800, - "description": "Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 70B instruct-tuned version is optimized for high quality dialogue usecases.\n\nIt has demonstrated strong performance compared to leading closed-source models in human evaluations.\n\nTo read more about the model release, [click here](https://ai.meta.com/blog/meta-llama-3-1/). Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).", - "context_length": 131072, + "description": "Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 8B instruct-tuned version is fast and efficient.\n\nIt has demonstrated strong performance compared to leading closed-source models in human evaluations.\n\nTo read more about the model release, [click here](https://ai.meta.com/blog/meta-llama-3-1/). Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).", + "context_length": 16384, "architecture": { "modality": "text->text", "input_modalities": [ @@ -15800,22 +15675,23 @@ "instruct_type": "llama3" }, "pricing": { - "prompt": "0.0000004", - "completion": "0.0000004", + "prompt": "0.00000002", + "completion": "0.00000005", "request": "0", "image": "0", "web_search": "0", "internal_reasoning": "0" }, "top_provider": { - "context_length": 131072, - "max_completion_tokens": null, + "context_length": 16384, + "max_completion_tokens": 16384, "is_moderated": false }, "per_request_limits": null, "supported_parameters": [ "frequency_penalty", "logit_bias", + "logprobs", "max_tokens", "min_p", "presence_penalty", @@ -15823,13 +15699,16 @@ "response_format", "seed", "stop", + "structured_outputs", "temperature", "tool_choice", "tools", "top_k", + "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "mistralai/mistral-nemo", @@ -15882,62 +15761,8 @@ ], "default_parameters": { "temperature": 0.3 - } - }, - { - "id": "openai/gpt-4o-mini-2024-07-18", - "canonical_slug": "openai/gpt-4o-mini-2024-07-18", - "hugging_face_id": null, - "name": "OpenAI: GPT-4o-mini (2024-07-18)", - "created": 1721260800, - "description": "GPT-4o mini is OpenAI's newest model after [GPT-4 Omni](/models/openai/gpt-4o), supporting both text and image inputs with text outputs.\n\nAs their most advanced small model, it is many multiples more affordable than other recent frontier models, and more than 60% cheaper than [GPT-3.5 Turbo](/models/openai/gpt-3.5-turbo). It maintains SOTA intelligence, while being significantly more cost-effective.\n\nGPT-4o mini achieves an 82% score on MMLU and presently ranks higher than GPT-4 on chat preferences [common leaderboards](https://arena.lmsys.org/).\n\nCheck out the [launch announcement](https://openai.com/index/gpt-4o-mini-advancing-cost-efficient-intelligence/) to learn more.\n\n#multimodal", - "context_length": 128000, - "architecture": { - "modality": "text+image->text", - "input_modalities": [ - "text", - "image", - "file" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "GPT", - "instruct_type": null }, - "pricing": { - "prompt": "0.00000015", - "completion": "0.0000006", - "request": "0", - "image": "0.007225", - "web_search": "0", - "internal_reasoning": "0", - "input_cache_read": "0.000000075" - }, - "top_provider": { - "context_length": 128000, - "max_completion_tokens": 16384, - "is_moderated": true - }, - "per_request_limits": null, - "supported_parameters": [ - "frequency_penalty", - "logit_bias", - "logprobs", - "max_tokens", - "presence_penalty", - "response_format", - "seed", - "stop", - "structured_outputs", - "temperature", - "tool_choice", - "tools", - "top_logprobs", - "top_p", - "web_search_options" - ], - "default_parameters": {} + "expiration_date": null }, { "id": "openai/gpt-4o-mini", @@ -15948,7 +15773,7 @@ "description": "GPT-4o mini is OpenAI's newest model after [GPT-4 Omni](/models/openai/gpt-4o), supporting both text and image inputs with text outputs.\n\nAs their most advanced small model, it is many multiples more affordable than other recent frontier models, and more than 60% cheaper than [GPT-3.5 Turbo](/models/openai/gpt-3.5-turbo). It maintains SOTA intelligence, while being significantly more cost-effective.\n\nGPT-4o mini achieves an 82% score on MMLU and presently ranks higher than GPT-4 on chat preferences [common leaderboards](https://arena.lmsys.org/).\n\nCheck out the [launch announcement](https://openai.com/index/gpt-4o-mini-advancing-cost-efficient-intelligence/) to learn more.\n\n#multimodal", "context_length": 128000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "text", "image", @@ -15963,10 +15788,6 @@ "pricing": { "prompt": "0.00000015", "completion": "0.0000006", - "request": "0", - "image": "0.000217", - "web_search": "0", - "internal_reasoning": "0", "input_cache_read": "0.000000075" }, "top_provider": { @@ -15992,7 +15813,60 @@ "top_p", "web_search_options" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null + }, + { + "id": "openai/gpt-4o-mini-2024-07-18", + "canonical_slug": "openai/gpt-4o-mini-2024-07-18", + "hugging_face_id": null, + "name": "OpenAI: GPT-4o-mini (2024-07-18)", + "created": 1721260800, + "description": "GPT-4o mini is OpenAI's newest model after [GPT-4 Omni](/models/openai/gpt-4o), supporting both text and image inputs with text outputs.\n\nAs their most advanced small model, it is many multiples more affordable than other recent frontier models, and more than 60% cheaper than [GPT-3.5 Turbo](/models/openai/gpt-3.5-turbo). It maintains SOTA intelligence, while being significantly more cost-effective.\n\nGPT-4o mini achieves an 82% score on MMLU and presently ranks higher than GPT-4 on chat preferences [common leaderboards](https://arena.lmsys.org/).\n\nCheck out the [launch announcement](https://openai.com/index/gpt-4o-mini-advancing-cost-efficient-intelligence/) to learn more.\n\n#multimodal", + "context_length": 128000, + "architecture": { + "modality": "text+image+file->text", + "input_modalities": [ + "text", + "image", + "file" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "GPT", + "instruct_type": null + }, + "pricing": { + "prompt": "0.00000015", + "completion": "0.0000006", + "input_cache_read": "0.000000075" + }, + "top_provider": { + "context_length": 128000, + "max_completion_tokens": 16384, + "is_moderated": true + }, + "per_request_limits": null, + "supported_parameters": [ + "frequency_penalty", + "logit_bias", + "logprobs", + "max_tokens", + "presence_penalty", + "response_format", + "seed", + "stop", + "structured_outputs", + "temperature", + "tool_choice", + "tools", + "top_logprobs", + "top_p", + "web_search_options" + ], + "default_parameters": {}, + "expiration_date": null }, { "id": "google/gemma-2-27b-it", @@ -16015,11 +15889,7 @@ }, "pricing": { "prompt": "0.00000065", - "completion": "0.00000065", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.00000065" }, "top_provider": { "context_length": 8192, @@ -16037,7 +15907,8 @@ "temperature", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "google/gemma-2-9b-it", @@ -16081,7 +15952,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "sao10k/l3-euryale-70b", @@ -16129,107 +16001,8 @@ "top_k", "top_p" ], - "default_parameters": {} - }, - { - "id": "nousresearch/hermes-2-pro-llama-3-8b", - "canonical_slug": "nousresearch/hermes-2-pro-llama-3-8b", - "hugging_face_id": "NousResearch/Hermes-2-Pro-Llama-3-8B", - "name": "NousResearch: Hermes 2 Pro - Llama-3 8B", - "created": 1716768000, - "description": "Hermes 2 Pro is an upgraded, retrained version of Nous Hermes 2, consisting of an updated and cleaned version of the OpenHermes 2.5 Dataset, as well as a newly introduced Function Calling and JSON Mode dataset developed in-house.", - "context_length": 8192, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Llama3", - "instruct_type": "chatml" - }, - "pricing": { - "prompt": "0.000000025", - "completion": "0.00000008", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 8192, - "max_completion_tokens": 2048, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "frequency_penalty", - "max_tokens", - "presence_penalty", - "repetition_penalty", - "response_format", - "seed", - "stop", - "structured_outputs", - "temperature", - "top_k", - "top_p" - ], - "default_parameters": {} - }, - { - "id": "mistralai/mistral-7b-instruct:free", - "canonical_slug": "mistralai/mistral-7b-instruct", - "hugging_face_id": "mistralai/Mistral-7B-Instruct-v0.3", - "name": "Mistral: Mistral 7B Instruct (free)", - "created": 1716768000, - "description": "A high-performing, industry-standard 7.3B parameter model, with optimizations for speed and context length.\n\n*Mistral 7B Instruct has multiple version variants, and this is intended to be the latest version.*", - "context_length": 32768, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Mistral", - "instruct_type": "mistral" - }, - "pricing": { - "prompt": "0", - "completion": "0", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 32768, - "max_completion_tokens": 16384, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "frequency_penalty", - "max_tokens", - "min_p", - "presence_penalty", - "repetition_penalty", - "response_format", - "seed", - "stop", - "temperature", - "tool_choice", - "tools", - "top_k", - "top_p" - ], - "default_parameters": { - "temperature": 0.3 - } + "default_parameters": {}, + "expiration_date": null }, { "id": "mistralai/mistral-7b-instruct", @@ -16251,8 +16024,8 @@ "instruct_type": "mistral" }, "pricing": { - "prompt": "0.000000028", - "completion": "0.000000054", + "prompt": "0.0000002", + "completion": "0.0000002", "request": "0", "image": "0", "web_search": "0", @@ -16260,7 +16033,7 @@ }, "top_provider": { "context_length": 32768, - "max_completion_tokens": 16384, + "max_completion_tokens": 4096, "is_moderated": false }, "per_request_limits": null, @@ -16271,18 +16044,64 @@ "min_p", "presence_penalty", "repetition_penalty", - "response_format", - "seed", "stop", "temperature", - "tool_choice", - "tools", "top_k", "top_p" ], "default_parameters": { "temperature": 0.3 - } + }, + "expiration_date": null + }, + { + "id": "nousresearch/hermes-2-pro-llama-3-8b", + "canonical_slug": "nousresearch/hermes-2-pro-llama-3-8b", + "hugging_face_id": "NousResearch/Hermes-2-Pro-Llama-3-8B", + "name": "NousResearch: Hermes 2 Pro - Llama-3 8B", + "created": 1716768000, + "description": "Hermes 2 Pro is an upgraded, retrained version of Nous Hermes 2, consisting of an updated and cleaned version of the OpenHermes 2.5 Dataset, as well as a newly introduced Function Calling and JSON Mode dataset developed in-house.", + "context_length": 8192, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Llama3", + "instruct_type": "chatml" + }, + "pricing": { + "prompt": "0.00000014", + "completion": "0.00000014", + "request": "0", + "image": "0", + "web_search": "0", + "internal_reasoning": "0" + }, + "top_provider": { + "context_length": 8192, + "max_completion_tokens": 8192, + "is_moderated": false + }, + "per_request_limits": null, + "supported_parameters": [ + "frequency_penalty", + "max_tokens", + "presence_penalty", + "repetition_penalty", + "response_format", + "seed", + "stop", + "structured_outputs", + "temperature", + "top_k", + "top_p" + ], + "default_parameters": {}, + "expiration_date": null }, { "id": "mistralai/mistral-7b-instruct-v0.3", @@ -16331,91 +16150,8 @@ ], "default_parameters": { "temperature": 0.3 - } - }, - { - "id": "microsoft/phi-3-mini-128k-instruct", - "canonical_slug": "microsoft/phi-3-mini-128k-instruct", - "hugging_face_id": "microsoft/Phi-3-mini-128k-instruct", - "name": "Microsoft: Phi-3 Mini 128K Instruct", - "created": 1716681600, - "description": "Phi-3 Mini is a powerful 3.8B parameter model designed for advanced language understanding, reasoning, and instruction following. Optimized through supervised fine-tuning and preference adjustments, it excels in tasks involving common sense, mathematics, logical reasoning, and code processing.\n\nAt time of release, Phi-3 Medium demonstrated state-of-the-art performance among lightweight models. This model is static, trained on an offline dataset with an October 2023 cutoff date.", - "context_length": 128000, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Other", - "instruct_type": "phi3" }, - "pricing": { - "prompt": "0.0000001", - "completion": "0.0000001", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 128000, - "max_completion_tokens": null, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "max_tokens", - "temperature", - "tool_choice", - "tools", - "top_p" - ], - "default_parameters": {} - }, - { - "id": "microsoft/phi-3-medium-128k-instruct", - "canonical_slug": "microsoft/phi-3-medium-128k-instruct", - "hugging_face_id": "microsoft/Phi-3-medium-128k-instruct", - "name": "Microsoft: Phi-3 Medium 128K Instruct", - "created": 1716508800, - "description": "Phi-3 128K Medium is a powerful 14-billion parameter model designed for advanced language understanding, reasoning, and instruction following. Optimized through supervised fine-tuning and preference adjustments, it excels in tasks involving common sense, mathematics, logical reasoning, and code processing.\n\nAt time of release, Phi-3 Medium demonstrated state-of-the-art performance among lightweight models. In the MMLU-Pro eval, the model even comes close to a Llama3 70B level of performance.\n\nFor 4k context length, try [Phi-3 Medium 4K](/models/microsoft/phi-3-medium-4k-instruct).", - "context_length": 128000, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Other", - "instruct_type": "phi3" - }, - "pricing": { - "prompt": "0.000001", - "completion": "0.000001", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 128000, - "max_completion_tokens": null, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "max_tokens", - "temperature", - "tool_choice", - "tools", - "top_p" - ], - "default_parameters": {} + "expiration_date": null }, { "id": "meta-llama/llama-guard-2-8b", @@ -16462,61 +16198,8 @@ "top_k", "top_p" ], - "default_parameters": {} - }, - { - "id": "openai/gpt-4o-2024-05-13", - "canonical_slug": "openai/gpt-4o-2024-05-13", - "hugging_face_id": null, - "name": "OpenAI: GPT-4o (2024-05-13)", - "created": 1715558400, - "description": "GPT-4o (\"o\" for \"omni\") is OpenAI's latest AI model, supporting both text and image inputs with text outputs. It maintains the intelligence level of [GPT-4 Turbo](/models/openai/gpt-4-turbo) while being twice as fast and 50% more cost-effective. GPT-4o also offers improved performance in processing non-English languages and enhanced visual capabilities.\n\nFor benchmarking against other models, it was briefly called [\"im-also-a-good-gpt2-chatbot\"](https://twitter.com/LiamFedus/status/1790064963966370209)\n\n#multimodal", - "context_length": 128000, - "architecture": { - "modality": "text+image->text", - "input_modalities": [ - "text", - "image", - "file" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "GPT", - "instruct_type": null - }, - "pricing": { - "prompt": "0.000005", - "completion": "0.000015", - "request": "0", - "image": "0.007225", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 128000, - "max_completion_tokens": 4096, - "is_moderated": true - }, - "per_request_limits": null, - "supported_parameters": [ - "frequency_penalty", - "logit_bias", - "logprobs", - "max_tokens", - "presence_penalty", - "response_format", - "seed", - "stop", - "structured_outputs", - "temperature", - "tool_choice", - "tools", - "top_logprobs", - "top_p", - "web_search_options" - ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "openai/gpt-4o", @@ -16527,7 +16210,7 @@ "description": "GPT-4o (\"o\" for \"omni\") is OpenAI's latest AI model, supporting both text and image inputs with text outputs. It maintains the intelligence level of [GPT-4 Turbo](/models/openai/gpt-4-turbo) while being twice as fast and 50% more cost-effective. GPT-4o also offers improved performance in processing non-English languages and enhanced visual capabilities.\n\nFor benchmarking against other models, it was briefly called [\"im-also-a-good-gpt2-chatbot\"](https://twitter.com/LiamFedus/status/1790064963966370209)\n\n#multimodal", "context_length": 128000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "text", "image", @@ -16542,10 +16225,6 @@ "pricing": { "prompt": "0.0000025", "completion": "0.00001", - "request": "0", - "image": "0.003613", - "web_search": "0", - "internal_reasoning": "0", "input_cache_read": "0.00000125" }, "top_provider": { @@ -16571,7 +16250,8 @@ "top_p", "web_search_options" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "openai/gpt-4o:extended", @@ -16582,7 +16262,7 @@ "description": "GPT-4o (\"o\" for \"omni\") is OpenAI's latest AI model, supporting both text and image inputs with text outputs. It maintains the intelligence level of [GPT-4 Turbo](/models/openai/gpt-4-turbo) while being twice as fast and 50% more cost-effective. GPT-4o also offers improved performance in processing non-English languages and enhanced visual capabilities.\n\nFor benchmarking against other models, it was briefly called [\"im-also-a-good-gpt2-chatbot\"](https://twitter.com/LiamFedus/status/1790064963966370209)\n\n#multimodal", "context_length": 128000, "architecture": { - "modality": "text+image->text", + "modality": "text+image+file->text", "input_modalities": [ "text", "image", @@ -16596,11 +16276,7 @@ }, "pricing": { "prompt": "0.000006", - "completion": "0.000018", - "request": "0", - "image": "0.007225", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.000018" }, "top_provider": { "context_length": 128000, @@ -16625,48 +16301,46 @@ "top_p", "web_search_options" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { - "id": "meta-llama/llama-3-70b-instruct", - "canonical_slug": "meta-llama/llama-3-70b-instruct", - "hugging_face_id": "meta-llama/Meta-Llama-3-70B-Instruct", - "name": "Meta: Llama 3 70B Instruct", - "created": 1713398400, - "description": "Meta's latest class of model (Llama 3) launched with a variety of sizes & flavors. This 70B instruct-tuned version was optimized for high quality dialogue usecases.\n\nIt has demonstrated strong performance compared to leading closed-source models in human evaluations.\n\nTo read more about the model release, [click here](https://ai.meta.com/blog/meta-llama-3/). Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).", - "context_length": 8192, + "id": "openai/gpt-4o-2024-05-13", + "canonical_slug": "openai/gpt-4o-2024-05-13", + "hugging_face_id": null, + "name": "OpenAI: GPT-4o (2024-05-13)", + "created": 1715558400, + "description": "GPT-4o (\"o\" for \"omni\") is OpenAI's latest AI model, supporting both text and image inputs with text outputs. It maintains the intelligence level of [GPT-4 Turbo](/models/openai/gpt-4-turbo) while being twice as fast and 50% more cost-effective. GPT-4o also offers improved performance in processing non-English languages and enhanced visual capabilities.\n\nFor benchmarking against other models, it was briefly called [\"im-also-a-good-gpt2-chatbot\"](https://twitter.com/LiamFedus/status/1790064963966370209)\n\n#multimodal", + "context_length": 128000, "architecture": { - "modality": "text->text", + "modality": "text+image+file->text", "input_modalities": [ - "text" + "text", + "image", + "file" ], "output_modalities": [ "text" ], - "tokenizer": "Llama3", - "instruct_type": "llama3" + "tokenizer": "GPT", + "instruct_type": null }, "pricing": { - "prompt": "0.0000003", - "completion": "0.0000004", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "prompt": "0.000005", + "completion": "0.000015" }, "top_provider": { - "context_length": 8192, - "max_completion_tokens": 16384, - "is_moderated": false + "context_length": 128000, + "max_completion_tokens": 4096, + "is_moderated": true }, "per_request_limits": null, "supported_parameters": [ "frequency_penalty", "logit_bias", + "logprobs", "max_tokens", - "min_p", "presence_penalty", - "repetition_penalty", "response_format", "seed", "stop", @@ -16674,10 +16348,12 @@ "temperature", "tool_choice", "tools", - "top_k", - "top_p" + "top_logprobs", + "top_p", + "web_search_options" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "meta-llama/llama-3-8b-instruct", @@ -16728,7 +16404,59 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null + }, + { + "id": "meta-llama/llama-3-70b-instruct", + "canonical_slug": "meta-llama/llama-3-70b-instruct", + "hugging_face_id": "meta-llama/Meta-Llama-3-70B-Instruct", + "name": "Meta: Llama 3 70B Instruct", + "created": 1713398400, + "description": "Meta's latest class of model (Llama 3) launched with a variety of sizes & flavors. This 70B instruct-tuned version was optimized for high quality dialogue usecases.\n\nIt has demonstrated strong performance compared to leading closed-source models in human evaluations.\n\nTo read more about the model release, [click here](https://ai.meta.com/blog/meta-llama-3/). Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).", + "context_length": 8192, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Llama3", + "instruct_type": "llama3" + }, + "pricing": { + "prompt": "0.0000004", + "completion": "0.0000004", + "request": "0", + "image": "0", + "web_search": "0", + "internal_reasoning": "0" + }, + "top_provider": { + "context_length": 8192, + "max_completion_tokens": null, + "is_moderated": false + }, + "per_request_limits": null, + "supported_parameters": [ + "frequency_penalty", + "logit_bias", + "max_tokens", + "min_p", + "presence_penalty", + "repetition_penalty", + "response_format", + "seed", + "stop", + "structured_outputs", + "temperature", + "top_k", + "top_p" + ], + "default_parameters": {}, + "expiration_date": null }, { "id": "mistralai/mixtral-8x22b-instruct", @@ -16751,11 +16479,7 @@ }, "pricing": { "prompt": "0.000002", - "completion": "0.000006", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.000006" }, "top_provider": { "context_length": 65536, @@ -16778,7 +16502,8 @@ ], "default_parameters": { "temperature": 0.3 - } + }, + "expiration_date": null }, { "id": "microsoft/wizardlm-2-8x22b", @@ -16826,7 +16551,8 @@ "top_k", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "openai/gpt-4-turbo", @@ -16850,11 +16576,7 @@ }, "pricing": { "prompt": "0.00001", - "completion": "0.00003", - "request": "0", - "image": "0.01445", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.00003" }, "top_provider": { "context_length": 128000, @@ -16878,7 +16600,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "anthropic/claude-3-haiku", @@ -16903,10 +16626,6 @@ "pricing": { "prompt": "0.00000025", "completion": "0.00000125", - "request": "0", - "image": "0.0004", - "web_search": "0", - "internal_reasoning": "0", "input_cache_read": "0.00000003", "input_cache_write": "0.0000003" }, @@ -16925,54 +16644,8 @@ "top_k", "top_p" ], - "default_parameters": {} - }, - { - "id": "anthropic/claude-3-opus", - "canonical_slug": "anthropic/claude-3-opus", - "hugging_face_id": null, - "name": "Anthropic: Claude 3 Opus", - "created": 1709596800, - "description": "Claude 3 Opus is Anthropic's most powerful model for highly complex tasks. It boasts top-level performance, intelligence, fluency, and understanding.\n\nSee the launch announcement and benchmark results [here](https://www.anthropic.com/news/claude-3-family)\n\n#multimodal", - "context_length": 200000, - "architecture": { - "modality": "text+image->text", - "input_modalities": [ - "text", - "image" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Claude", - "instruct_type": null - }, - "pricing": { - "prompt": "0.000015", - "completion": "0.000075", - "request": "0", - "image": "0.024", - "web_search": "0", - "internal_reasoning": "0", - "input_cache_read": "0.0000015", - "input_cache_write": "0.00001875" - }, - "top_provider": { - "context_length": 200000, - "max_completion_tokens": 4096, - "is_moderated": true - }, - "per_request_limits": null, - "supported_parameters": [ - "max_tokens", - "stop", - "temperature", - "tool_choice", - "tools", - "top_k", - "top_p" - ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "mistralai/mistral-large", @@ -16995,11 +16668,7 @@ }, "pricing": { "prompt": "0.000002", - "completion": "0.000006", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.000006" }, "top_provider": { "context_length": 128000, @@ -17022,7 +16691,8 @@ ], "default_parameters": { "temperature": 0.3 - } + }, + "expiration_date": null }, { "id": "openai/gpt-3.5-turbo-0613", @@ -17073,7 +16743,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "openai/gpt-4-turbo-preview", @@ -17096,11 +16767,7 @@ }, "pricing": { "prompt": "0.00001", - "completion": "0.00003", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.00003" }, "top_provider": { "context_length": 128000, @@ -17124,7 +16791,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "mistralai/mistral-tiny", @@ -17147,11 +16815,7 @@ }, "pricing": { "prompt": "0.00000025", - "completion": "0.00000025", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.00000025" }, "top_provider": { "context_length": 32768, @@ -17174,7 +16838,8 @@ ], "default_parameters": { "temperature": 0.3 - } + }, + "expiration_date": null }, { "id": "mistralai/mistral-7b-instruct-v0.2", @@ -17223,7 +16888,8 @@ ], "default_parameters": { "temperature": 0.3 - } + }, + "expiration_date": null }, { "id": "mistralai/mixtral-8x7b-instruct", @@ -17276,7 +16942,8 @@ ], "default_parameters": { "temperature": 0.3 - } + }, + "expiration_date": null }, { "id": "neversleep/noromaid-20b", @@ -17299,11 +16966,7 @@ }, "pricing": { "prompt": "0.000001", - "completion": "0.00000175", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.00000175" }, "top_provider": { "context_length": 4096, @@ -17329,7 +16992,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "alpindale/goliath-120b", @@ -17351,8 +17015,8 @@ "instruct_type": "airoboros" }, "pricing": { - "prompt": "0.000006", - "completion": "0.000008", + "prompt": "0.00000375", + "completion": "0.0000075", "request": "0", "image": "0", "web_search": "0", @@ -17381,7 +17045,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "openrouter/auto", @@ -17389,7 +17054,7 @@ "hugging_face_id": null, "name": "Auto Router", "created": 1699401600, - "description": "Your prompt will be processed by a meta-model and routed to one of dozens of models (see below), optimizing for the best possible output.\n\nTo see which model was used, visit [Activity](/activity), or read the `model` attribute of the response. Your response will be priced at the same rate as the routed model.\n\nThe meta-model is powered by [Not Diamond](https://docs.notdiamond.ai/docs/how-not-diamond-works). Learn more in our [docs](/docs/model-routing).\n\nRequests will be routed to the following models:\n- [openai/gpt-5.1](/openai/gpt-5.1)\n- [openai/gpt-5](/openai/gpt-5)\n- [openai/gpt-5-mini](/openai/gpt-5-mini)\n- [openai/gpt-5-nano](/openai/gpt-5-nano)\n- [openai/gpt-4.1](/openai/gpt-4.1)\n- [openai/gpt-4.1-mini](/openai/gpt-4.1-mini)\n- [openai/gpt-4.1-nano](/openai/gpt-4.1-nano)\n- [openai/gpt-4o](/openai/gpt-4o)\n- [openai/gpt-4o-2024-05-13](/openai/gpt-4o-2024-05-13)\n- [openai/gpt-4o-2024-08-06](/openai/gpt-4o-2024-08-06)\n- [openai/gpt-4o-2024-11-20](/openai/gpt-4o-2024-11-20)\n- [openai/gpt-4o-mini](/openai/gpt-4o-mini)\n- [openai/gpt-4o-mini-2024-07-18](/openai/gpt-4o-mini-2024-07-18)\n- [openai/gpt-4-turbo](/openai/gpt-4-turbo)\n- [openai/gpt-4-turbo-preview](/openai/gpt-4-turbo-preview)\n- [openai/gpt-4-1106-preview](/openai/gpt-4-1106-preview)\n- [openai/gpt-4](/openai/gpt-4)\n- [openai/gpt-3.5-turbo](/openai/gpt-3.5-turbo)\n- [openai/gpt-oss-120b](/openai/gpt-oss-120b)\n- [anthropic/claude-opus-4.5](/anthropic/claude-opus-4.5)\n- [anthropic/claude-opus-4.1](/anthropic/claude-opus-4.1)\n- [anthropic/claude-opus-4](/anthropic/claude-opus-4)\n- [anthropic/claude-sonnet-4.5](/anthropic/claude-sonnet-4.5)\n- [anthropic/claude-sonnet-4](/anthropic/claude-sonnet-4)\n- [anthropic/claude-3.7-sonnet](/anthropic/claude-3.7-sonnet)\n- [anthropic/claude-haiku-4.5](/anthropic/claude-haiku-4.5)\n- [anthropic/claude-3.5-haiku](/anthropic/claude-3.5-haiku)\n- [anthropic/claude-3-haiku](/anthropic/claude-3-haiku)\n- [google/gemini-3-pro-preview](/google/gemini-3-pro-preview)\n- [google/gemini-2.5-pro](/google/gemini-2.5-pro)\n- [google/gemini-2.0-flash-001](/google/gemini-2.0-flash-001)\n- [google/gemini-2.5-flash](/google/gemini-2.5-flash)\n- [mistralai/mistral-large](/mistralai/mistral-large)\n- [mistralai/mistral-large-2407](/mistralai/mistral-large-2407)\n- [mistralai/mistral-large-2411](/mistralai/mistral-large-2411)\n- [mistralai/mistral-medium-3.1](/mistralai/mistral-medium-3.1)\n- [mistralai/mistral-nemo](/mistralai/mistral-nemo)\n- [mistralai/mistral-7b-instruct](/mistralai/mistral-7b-instruct)\n- [mistralai/mixtral-8x7b-instruct](/mistralai/mixtral-8x7b-instruct)\n- [mistralai/mixtral-8x22b-instruct](/mistralai/mixtral-8x22b-instruct)\n- [mistralai/codestral-2508](/mistralai/codestral-2508)\n- [x-ai/grok-4](/x-ai/grok-4)\n- [x-ai/grok-3](/x-ai/grok-3)\n- [x-ai/grok-3-mini](/x-ai/grok-3-mini)\n- [deepseek/deepseek-r1](/deepseek/deepseek-r1)\n- [meta-llama/llama-3.3-70b-instruct](/meta-llama/llama-3.3-70b-instruct)\n- [meta-llama/llama-3.1-405b-instruct](/meta-llama/llama-3.1-405b-instruct)\n- [meta-llama/llama-3.1-70b-instruct](/meta-llama/llama-3.1-70b-instruct)\n- [meta-llama/llama-3.1-8b-instruct](/meta-llama/llama-3.1-8b-instruct)\n- [meta-llama/llama-3-70b-instruct](/meta-llama/llama-3-70b-instruct)\n- [meta-llama/llama-3-8b-instruct](/meta-llama/llama-3-8b-instruct)\n- [qwen/qwen3-235b-a22b](/qwen/qwen3-235b-a22b)\n- [qwen/qwen3-32b](/qwen/qwen3-32b)\n- [qwen/qwen3-14b](/qwen/qwen3-14b)\n- [cohere/command-r-plus-08-2024](/cohere/command-r-plus-08-2024)\n- [cohere/command-r-08-2024](/cohere/command-r-08-2024)\n- [moonshotai/kimi-k2-thinking](/moonshotai/kimi-k2-thinking)\n- [perplexity/sonar](/perplexity/sonar)", + "description": "Your prompt will be processed by a meta-model and routed to one of dozens of models (see below), optimizing for the best possible output.\n\nTo see which model was used, visit [Activity](/activity), or read the `model` attribute of the response. Your response will be priced at the same rate as the routed model.\n\nLearn more, including how to customize the models for routing, in our [docs](/docs/guides/routing/routers/auto-router).\n\nRequests will be routed to the following models:\n- [openai/gpt-5.1](/openai/gpt-5.1)\n- [openai/gpt-5](/openai/gpt-5)\n- [openai/gpt-5-mini](/openai/gpt-5-mini)\n- [openai/gpt-5-nano](/openai/gpt-5-nano)\n- [openai/gpt-4.1](/openai/gpt-4.1)\n- [openai/gpt-4.1-mini](/openai/gpt-4.1-mini)\n- [openai/gpt-4.1-nano](/openai/gpt-4.1-nano)\n- [openai/gpt-4o](/openai/gpt-4o)\n- [openai/gpt-4o-2024-05-13](/openai/gpt-4o-2024-05-13)\n- [openai/gpt-4o-2024-08-06](/openai/gpt-4o-2024-08-06)\n- [openai/gpt-4o-2024-11-20](/openai/gpt-4o-2024-11-20)\n- [openai/gpt-4o-mini](/openai/gpt-4o-mini)\n- [openai/gpt-4o-mini-2024-07-18](/openai/gpt-4o-mini-2024-07-18)\n- [openai/gpt-4-turbo](/openai/gpt-4-turbo)\n- [openai/gpt-4-turbo-preview](/openai/gpt-4-turbo-preview)\n- [openai/gpt-4-1106-preview](/openai/gpt-4-1106-preview)\n- [openai/gpt-4](/openai/gpt-4)\n- [openai/gpt-3.5-turbo](/openai/gpt-3.5-turbo)\n- [openai/gpt-oss-120b](/openai/gpt-oss-120b)\n- [anthropic/claude-opus-4.5](/anthropic/claude-opus-4.5)\n- [anthropic/claude-opus-4.1](/anthropic/claude-opus-4.1)\n- [anthropic/claude-opus-4](/anthropic/claude-opus-4)\n- [anthropic/claude-sonnet-4.5](/anthropic/claude-sonnet-4.5)\n- [anthropic/claude-sonnet-4](/anthropic/claude-sonnet-4)\n- [anthropic/claude-3.7-sonnet](/anthropic/claude-3.7-sonnet)\n- [anthropic/claude-haiku-4.5](/anthropic/claude-haiku-4.5)\n- [anthropic/claude-3.5-haiku](/anthropic/claude-3.5-haiku)\n- [anthropic/claude-3-haiku](/anthropic/claude-3-haiku)\n- [google/gemini-3-pro-preview](/google/gemini-3-pro-preview)\n- [google/gemini-2.5-pro](/google/gemini-2.5-pro)\n- [google/gemini-2.0-flash-001](/google/gemini-2.0-flash-001)\n- [google/gemini-2.5-flash](/google/gemini-2.5-flash)\n- [mistralai/mistral-large](/mistralai/mistral-large)\n- [mistralai/mistral-large-2407](/mistralai/mistral-large-2407)\n- [mistralai/mistral-large-2411](/mistralai/mistral-large-2411)\n- [mistralai/mistral-medium-3.1](/mistralai/mistral-medium-3.1)\n- [mistralai/mistral-nemo](/mistralai/mistral-nemo)\n- [mistralai/mistral-7b-instruct](/mistralai/mistral-7b-instruct)\n- [mistralai/mixtral-8x7b-instruct](/mistralai/mixtral-8x7b-instruct)\n- [mistralai/mixtral-8x22b-instruct](/mistralai/mixtral-8x22b-instruct)\n- [mistralai/codestral-2508](/mistralai/codestral-2508)\n- [x-ai/grok-4](/x-ai/grok-4)\n- [x-ai/grok-3](/x-ai/grok-3)\n- [x-ai/grok-3-mini](/x-ai/grok-3-mini)\n- [deepseek/deepseek-r1](/deepseek/deepseek-r1)\n- [meta-llama/llama-3.3-70b-instruct](/meta-llama/llama-3.3-70b-instruct)\n- [meta-llama/llama-3.1-405b-instruct](/meta-llama/llama-3.1-405b-instruct)\n- [meta-llama/llama-3.1-70b-instruct](/meta-llama/llama-3.1-70b-instruct)\n- [meta-llama/llama-3.1-8b-instruct](/meta-llama/llama-3.1-8b-instruct)\n- [meta-llama/llama-3-70b-instruct](/meta-llama/llama-3-70b-instruct)\n- [meta-llama/llama-3-8b-instruct](/meta-llama/llama-3-8b-instruct)\n- [qwen/qwen3-235b-a22b](/qwen/qwen3-235b-a22b)\n- [qwen/qwen3-32b](/qwen/qwen3-32b)\n- [qwen/qwen3-14b](/qwen/qwen3-14b)\n- [cohere/command-r-plus-08-2024](/cohere/command-r-plus-08-2024)\n- [cohere/command-r-08-2024](/cohere/command-r-08-2024)\n- [moonshotai/kimi-k2-thinking](/moonshotai/kimi-k2-thinking)\n- [perplexity/sonar](/perplexity/sonar)", "context_length": 2000000, "architecture": { "modality": "text->text", @@ -17413,7 +17078,12 @@ }, "per_request_limits": null, "supported_parameters": [], - "default_parameters": {} + "default_parameters": { + "temperature": null, + "top_p": null, + "frequency_penalty": null + }, + "expiration_date": null }, { "id": "openai/gpt-4-1106-preview", @@ -17436,11 +17106,7 @@ }, "pricing": { "prompt": "0.00001", - "completion": "0.00003", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.00003" }, "top_provider": { "context_length": 128000, @@ -17464,7 +17130,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "openai/gpt-3.5-turbo-instruct", @@ -17487,11 +17154,7 @@ }, "pricing": { "prompt": "0.0000015", - "completion": "0.000002", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.000002" }, "top_provider": { "context_length": 4095, @@ -17513,7 +17176,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "mistralai/mistral-7b-instruct-v0.1", @@ -17560,7 +17224,8 @@ ], "default_parameters": { "temperature": 0.3 - } + }, + "expiration_date": null }, { "id": "openai/gpt-3.5-turbo-16k", @@ -17583,11 +17248,7 @@ }, "pricing": { "prompt": "0.000003", - "completion": "0.000004", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.000004" }, "top_provider": { "context_length": 16385, @@ -17611,7 +17272,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "mancer/weaver", @@ -17663,7 +17325,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "undi95/remm-slerp-l2-13b", @@ -17686,11 +17349,7 @@ }, "pricing": { "prompt": "0.00000045", - "completion": "0.00000065", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.00000065" }, "top_provider": { "context_length": 6144, @@ -17716,7 +17375,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "gryphe/mythomax-l2-13b", @@ -17739,11 +17399,7 @@ }, "pricing": { "prompt": "0.00000006", - "completion": "0.00000006", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.00000006" }, "top_provider": { "context_length": 4096, @@ -17769,7 +17425,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "openai/gpt-4-0314", @@ -17792,11 +17449,7 @@ }, "pricing": { "prompt": "0.00003", - "completion": "0.00006", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.00006" }, "top_provider": { "context_length": 8191, @@ -17820,7 +17473,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "openai/gpt-4", @@ -17843,11 +17497,7 @@ }, "pricing": { "prompt": "0.00003", - "completion": "0.00006", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.00006" }, "top_provider": { "context_length": 8191, @@ -17871,7 +17521,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null }, { "id": "openai/gpt-3.5-turbo", @@ -17894,11 +17545,7 @@ }, "pricing": { "prompt": "0.0000005", - "completion": "0.0000015", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" + "completion": "0.0000015" }, "top_provider": { "context_length": 16385, @@ -17922,7 +17569,8 @@ "top_logprobs", "top_p" ], - "default_parameters": {} + "default_parameters": {}, + "expiration_date": null } ] } \ No newline at end of file diff --git a/packages/kbot/dist-in/models/cache/openai-models.d.ts b/packages/kbot/dist-in/models/cache/openai-models.d.ts index eb82796b..de52a027 100644 --- a/packages/kbot/dist-in/models/cache/openai-models.d.ts +++ b/packages/kbot/dist-in/models/cache/openai-models.d.ts @@ -2,11 +2,11 @@ export declare enum E_OPENAI_MODEL { MODEL_GPT_4_0613 = "gpt-4-0613", MODEL_GPT_4 = "gpt-4", MODEL_GPT_3_5_TURBO = "gpt-3.5-turbo", - MODEL_GPT_AUDIO = "gpt-audio", - MODEL_GPT_5_NANO = "gpt-5-nano", - MODEL_GPT_AUDIO_2025_08_28 = "gpt-audio-2025-08-28", - MODEL_GPT_REALTIME = "gpt-realtime", - MODEL_GPT_REALTIME_2025_08_28 = "gpt-realtime-2025-08-28", + MODEL_CHATGPT_IMAGE_LATEST = "chatgpt-image-latest", + MODEL_GPT_4O_MINI_TTS_2025_03_20 = "gpt-4o-mini-tts-2025-03-20", + MODEL_GPT_4O_MINI_TTS_2025_12_15 = "gpt-4o-mini-tts-2025-12-15", + MODEL_GPT_REALTIME_MINI_2025_12_15 = "gpt-realtime-mini-2025-12-15", + MODEL_GPT_AUDIO_MINI_2025_12_15 = "gpt-audio-mini-2025-12-15", MODEL_DAVINCI_002 = "davinci-002", MODEL_BABBAGE_002 = "babbage-002", MODEL_GPT_3_5_TURBO_INSTRUCT = "gpt-3.5-turbo-instruct", @@ -31,10 +31,6 @@ export declare enum E_OPENAI_MODEL { MODEL_GPT_4O_MINI = "gpt-4o-mini", MODEL_GPT_4O_2024_08_06 = "gpt-4o-2024-08-06", MODEL_CHATGPT_4O_LATEST = "chatgpt-4o-latest", - MODEL_O1_MINI_2024_09_12 = "o1-mini-2024-09-12", - MODEL_O1_MINI = "o1-mini", - MODEL_GPT_4O_REALTIME_PREVIEW_2024_10_01 = "gpt-4o-realtime-preview-2024-10-01", - MODEL_GPT_4O_AUDIO_PREVIEW_2024_10_01 = "gpt-4o-audio-preview-2024-10-01", MODEL_GPT_4O_AUDIO_PREVIEW = "gpt-4o-audio-preview", MODEL_GPT_4O_REALTIME_PREVIEW = "gpt-4o-realtime-preview", MODEL_OMNI_MODERATION_LATEST = "omni-moderation-latest", @@ -74,6 +70,7 @@ export declare enum E_OPENAI_MODEL { MODEL_GPT_4O_REALTIME_PREVIEW_2025_06_03 = "gpt-4o-realtime-preview-2025-06-03", MODEL_GPT_4O_AUDIO_PREVIEW_2025_06_03 = "gpt-4o-audio-preview-2025-06-03", MODEL_O4_MINI_DEEP_RESEARCH = "o4-mini-deep-research", + MODEL_GPT_4O_TRANSCRIBE_DIARIZE = "gpt-4o-transcribe-diarize", MODEL_O4_MINI_DEEP_RESEARCH_2025_06_26 = "o4-mini-deep-research-2025-06-26", MODEL_GPT_5_CHAT_LATEST = "gpt-5-chat-latest", MODEL_GPT_5_2025_08_07 = "gpt-5-2025-08-07", @@ -81,6 +78,37 @@ export declare enum E_OPENAI_MODEL { MODEL_GPT_5_MINI_2025_08_07 = "gpt-5-mini-2025-08-07", MODEL_GPT_5_MINI = "gpt-5-mini", MODEL_GPT_5_NANO_2025_08_07 = "gpt-5-nano-2025-08-07", + MODEL_GPT_5_NANO = "gpt-5-nano", + MODEL_GPT_AUDIO_2025_08_28 = "gpt-audio-2025-08-28", + MODEL_GPT_REALTIME = "gpt-realtime", + MODEL_GPT_REALTIME_2025_08_28 = "gpt-realtime-2025-08-28", + MODEL_GPT_AUDIO = "gpt-audio", + MODEL_GPT_5_CODEX = "gpt-5-codex", + MODEL_GPT_IMAGE_1_MINI = "gpt-image-1-mini", + MODEL_GPT_5_PRO_2025_10_06 = "gpt-5-pro-2025-10-06", + MODEL_GPT_5_PRO = "gpt-5-pro", + MODEL_GPT_AUDIO_MINI = "gpt-audio-mini", + MODEL_GPT_AUDIO_MINI_2025_10_06 = "gpt-audio-mini-2025-10-06", + MODEL_GPT_5_SEARCH_API = "gpt-5-search-api", + MODEL_GPT_REALTIME_MINI = "gpt-realtime-mini", + MODEL_GPT_REALTIME_MINI_2025_10_06 = "gpt-realtime-mini-2025-10-06", + MODEL_SORA_2 = "sora-2", + MODEL_SORA_2_PRO = "sora-2-pro", + MODEL_GPT_5_SEARCH_API_2025_10_14 = "gpt-5-search-api-2025-10-14", + MODEL_GPT_5_1_CHAT_LATEST = "gpt-5.1-chat-latest", + MODEL_GPT_5_1_2025_11_13 = "gpt-5.1-2025-11-13", + MODEL_GPT_5_1 = "gpt-5.1", + MODEL_GPT_5_1_CODEX = "gpt-5.1-codex", + MODEL_GPT_5_1_CODEX_MINI = "gpt-5.1-codex-mini", + MODEL_GPT_5_1_CODEX_MAX = "gpt-5.1-codex-max", + MODEL_GPT_IMAGE_1_5 = "gpt-image-1.5", + MODEL_GPT_5_2_2025_12_11 = "gpt-5.2-2025-12-11", + MODEL_GPT_5_2 = "gpt-5.2", + MODEL_GPT_5_2_PRO_2025_12_11 = "gpt-5.2-pro-2025-12-11", + MODEL_GPT_5_2_PRO = "gpt-5.2-pro", + MODEL_GPT_5_2_CHAT_LATEST = "gpt-5.2-chat-latest", + MODEL_GPT_4O_MINI_TRANSCRIBE_2025_12_15 = "gpt-4o-mini-transcribe-2025-12-15", + MODEL_GPT_4O_MINI_TRANSCRIBE_2025_03_20 = "gpt-4o-mini-transcribe-2025-03-20", MODEL_GPT_3_5_TURBO_16K = "gpt-3.5-turbo-16k", MODEL_TTS_1 = "tts-1", MODEL_WHISPER_1 = "whisper-1", diff --git a/packages/kbot/dist-in/models/cache/openai-models.js b/packages/kbot/dist-in/models/cache/openai-models.js index 378972b2..a812120d 100644 --- a/packages/kbot/dist-in/models/cache/openai-models.js +++ b/packages/kbot/dist-in/models/cache/openai-models.js @@ -3,11 +3,11 @@ export var E_OPENAI_MODEL; E_OPENAI_MODEL["MODEL_GPT_4_0613"] = "gpt-4-0613"; E_OPENAI_MODEL["MODEL_GPT_4"] = "gpt-4"; E_OPENAI_MODEL["MODEL_GPT_3_5_TURBO"] = "gpt-3.5-turbo"; - E_OPENAI_MODEL["MODEL_GPT_AUDIO"] = "gpt-audio"; - E_OPENAI_MODEL["MODEL_GPT_5_NANO"] = "gpt-5-nano"; - E_OPENAI_MODEL["MODEL_GPT_AUDIO_2025_08_28"] = "gpt-audio-2025-08-28"; - E_OPENAI_MODEL["MODEL_GPT_REALTIME"] = "gpt-realtime"; - E_OPENAI_MODEL["MODEL_GPT_REALTIME_2025_08_28"] = "gpt-realtime-2025-08-28"; + E_OPENAI_MODEL["MODEL_CHATGPT_IMAGE_LATEST"] = "chatgpt-image-latest"; + E_OPENAI_MODEL["MODEL_GPT_4O_MINI_TTS_2025_03_20"] = "gpt-4o-mini-tts-2025-03-20"; + E_OPENAI_MODEL["MODEL_GPT_4O_MINI_TTS_2025_12_15"] = "gpt-4o-mini-tts-2025-12-15"; + E_OPENAI_MODEL["MODEL_GPT_REALTIME_MINI_2025_12_15"] = "gpt-realtime-mini-2025-12-15"; + E_OPENAI_MODEL["MODEL_GPT_AUDIO_MINI_2025_12_15"] = "gpt-audio-mini-2025-12-15"; E_OPENAI_MODEL["MODEL_DAVINCI_002"] = "davinci-002"; E_OPENAI_MODEL["MODEL_BABBAGE_002"] = "babbage-002"; E_OPENAI_MODEL["MODEL_GPT_3_5_TURBO_INSTRUCT"] = "gpt-3.5-turbo-instruct"; @@ -32,10 +32,6 @@ export var E_OPENAI_MODEL; E_OPENAI_MODEL["MODEL_GPT_4O_MINI"] = "gpt-4o-mini"; E_OPENAI_MODEL["MODEL_GPT_4O_2024_08_06"] = "gpt-4o-2024-08-06"; E_OPENAI_MODEL["MODEL_CHATGPT_4O_LATEST"] = "chatgpt-4o-latest"; - E_OPENAI_MODEL["MODEL_O1_MINI_2024_09_12"] = "o1-mini-2024-09-12"; - E_OPENAI_MODEL["MODEL_O1_MINI"] = "o1-mini"; - E_OPENAI_MODEL["MODEL_GPT_4O_REALTIME_PREVIEW_2024_10_01"] = "gpt-4o-realtime-preview-2024-10-01"; - E_OPENAI_MODEL["MODEL_GPT_4O_AUDIO_PREVIEW_2024_10_01"] = "gpt-4o-audio-preview-2024-10-01"; E_OPENAI_MODEL["MODEL_GPT_4O_AUDIO_PREVIEW"] = "gpt-4o-audio-preview"; E_OPENAI_MODEL["MODEL_GPT_4O_REALTIME_PREVIEW"] = "gpt-4o-realtime-preview"; E_OPENAI_MODEL["MODEL_OMNI_MODERATION_LATEST"] = "omni-moderation-latest"; @@ -75,6 +71,7 @@ export var E_OPENAI_MODEL; E_OPENAI_MODEL["MODEL_GPT_4O_REALTIME_PREVIEW_2025_06_03"] = "gpt-4o-realtime-preview-2025-06-03"; E_OPENAI_MODEL["MODEL_GPT_4O_AUDIO_PREVIEW_2025_06_03"] = "gpt-4o-audio-preview-2025-06-03"; E_OPENAI_MODEL["MODEL_O4_MINI_DEEP_RESEARCH"] = "o4-mini-deep-research"; + E_OPENAI_MODEL["MODEL_GPT_4O_TRANSCRIBE_DIARIZE"] = "gpt-4o-transcribe-diarize"; E_OPENAI_MODEL["MODEL_O4_MINI_DEEP_RESEARCH_2025_06_26"] = "o4-mini-deep-research-2025-06-26"; E_OPENAI_MODEL["MODEL_GPT_5_CHAT_LATEST"] = "gpt-5-chat-latest"; E_OPENAI_MODEL["MODEL_GPT_5_2025_08_07"] = "gpt-5-2025-08-07"; @@ -82,9 +79,40 @@ export var E_OPENAI_MODEL; E_OPENAI_MODEL["MODEL_GPT_5_MINI_2025_08_07"] = "gpt-5-mini-2025-08-07"; E_OPENAI_MODEL["MODEL_GPT_5_MINI"] = "gpt-5-mini"; E_OPENAI_MODEL["MODEL_GPT_5_NANO_2025_08_07"] = "gpt-5-nano-2025-08-07"; + E_OPENAI_MODEL["MODEL_GPT_5_NANO"] = "gpt-5-nano"; + E_OPENAI_MODEL["MODEL_GPT_AUDIO_2025_08_28"] = "gpt-audio-2025-08-28"; + E_OPENAI_MODEL["MODEL_GPT_REALTIME"] = "gpt-realtime"; + E_OPENAI_MODEL["MODEL_GPT_REALTIME_2025_08_28"] = "gpt-realtime-2025-08-28"; + E_OPENAI_MODEL["MODEL_GPT_AUDIO"] = "gpt-audio"; + E_OPENAI_MODEL["MODEL_GPT_5_CODEX"] = "gpt-5-codex"; + E_OPENAI_MODEL["MODEL_GPT_IMAGE_1_MINI"] = "gpt-image-1-mini"; + E_OPENAI_MODEL["MODEL_GPT_5_PRO_2025_10_06"] = "gpt-5-pro-2025-10-06"; + E_OPENAI_MODEL["MODEL_GPT_5_PRO"] = "gpt-5-pro"; + E_OPENAI_MODEL["MODEL_GPT_AUDIO_MINI"] = "gpt-audio-mini"; + E_OPENAI_MODEL["MODEL_GPT_AUDIO_MINI_2025_10_06"] = "gpt-audio-mini-2025-10-06"; + E_OPENAI_MODEL["MODEL_GPT_5_SEARCH_API"] = "gpt-5-search-api"; + E_OPENAI_MODEL["MODEL_GPT_REALTIME_MINI"] = "gpt-realtime-mini"; + E_OPENAI_MODEL["MODEL_GPT_REALTIME_MINI_2025_10_06"] = "gpt-realtime-mini-2025-10-06"; + E_OPENAI_MODEL["MODEL_SORA_2"] = "sora-2"; + E_OPENAI_MODEL["MODEL_SORA_2_PRO"] = "sora-2-pro"; + E_OPENAI_MODEL["MODEL_GPT_5_SEARCH_API_2025_10_14"] = "gpt-5-search-api-2025-10-14"; + E_OPENAI_MODEL["MODEL_GPT_5_1_CHAT_LATEST"] = "gpt-5.1-chat-latest"; + E_OPENAI_MODEL["MODEL_GPT_5_1_2025_11_13"] = "gpt-5.1-2025-11-13"; + E_OPENAI_MODEL["MODEL_GPT_5_1"] = "gpt-5.1"; + E_OPENAI_MODEL["MODEL_GPT_5_1_CODEX"] = "gpt-5.1-codex"; + E_OPENAI_MODEL["MODEL_GPT_5_1_CODEX_MINI"] = "gpt-5.1-codex-mini"; + E_OPENAI_MODEL["MODEL_GPT_5_1_CODEX_MAX"] = "gpt-5.1-codex-max"; + E_OPENAI_MODEL["MODEL_GPT_IMAGE_1_5"] = "gpt-image-1.5"; + E_OPENAI_MODEL["MODEL_GPT_5_2_2025_12_11"] = "gpt-5.2-2025-12-11"; + E_OPENAI_MODEL["MODEL_GPT_5_2"] = "gpt-5.2"; + E_OPENAI_MODEL["MODEL_GPT_5_2_PRO_2025_12_11"] = "gpt-5.2-pro-2025-12-11"; + E_OPENAI_MODEL["MODEL_GPT_5_2_PRO"] = "gpt-5.2-pro"; + E_OPENAI_MODEL["MODEL_GPT_5_2_CHAT_LATEST"] = "gpt-5.2-chat-latest"; + E_OPENAI_MODEL["MODEL_GPT_4O_MINI_TRANSCRIBE_2025_12_15"] = "gpt-4o-mini-transcribe-2025-12-15"; + E_OPENAI_MODEL["MODEL_GPT_4O_MINI_TRANSCRIBE_2025_03_20"] = "gpt-4o-mini-transcribe-2025-03-20"; E_OPENAI_MODEL["MODEL_GPT_3_5_TURBO_16K"] = "gpt-3.5-turbo-16k"; E_OPENAI_MODEL["MODEL_TTS_1"] = "tts-1"; E_OPENAI_MODEL["MODEL_WHISPER_1"] = "whisper-1"; E_OPENAI_MODEL["MODEL_TEXT_EMBEDDING_ADA_002"] = "text-embedding-ada-002"; })(E_OPENAI_MODEL || (E_OPENAI_MODEL = {})); -//# 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\ No newline at end of file +//# 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\ No newline at end of file diff --git a/packages/kbot/dist-in/models/cache/openrouter-models-free.d.ts b/packages/kbot/dist-in/models/cache/openrouter-models-free.d.ts index 66099917..77d96090 100644 --- a/packages/kbot/dist-in/models/cache/openrouter-models-free.d.ts +++ b/packages/kbot/dist-in/models/cache/openrouter-models-free.d.ts @@ -1,7 +1,16 @@ export declare enum E_OPENROUTER_MODEL_FREE { - MODEL_FREE_X_AI_GROK_4_FAST_FREE = "x-ai/grok-4-fast:free", + MODEL_FREE_ALLENAI_OLMO_3_1_32B_THINK_FREE = "allenai/olmo-3.1-32b-think:free", + MODEL_FREE_XIAOMI_MIMO_V2_FLASH_FREE = "xiaomi/mimo-v2-flash:free", + MODEL_FREE_NVIDIA_NEMOTRON_3_NANO_30B_A3B_FREE = "nvidia/nemotron-3-nano-30b-a3b:free", + MODEL_FREE_MISTRALAI_DEVSTRAL_2512_FREE = "mistralai/devstral-2512:free", + MODEL_FREE_NEX_AGI_DEEPSEEK_V3_1_NEX_N1_FREE = "nex-agi/deepseek-v3.1-nex-n1:free", + MODEL_FREE_ARCEE_AI_TRINITY_MINI_FREE = "arcee-ai/trinity-mini:free", + MODEL_FREE_TNGTECH_TNG_R1T_CHIMERA_FREE = "tngtech/tng-r1t-chimera:free", + MODEL_FREE_ALLENAI_OLMO_3_32B_THINK_FREE = "allenai/olmo-3-32b-think:free", + MODEL_FREE_KWAIPILOT_KAT_CODER_PRO_FREE = "kwaipilot/kat-coder-pro:free", + MODEL_FREE_NVIDIA_NEMOTRON_NANO_12B_V2_VL_FREE = "nvidia/nemotron-nano-12b-v2-vl:free", + MODEL_FREE_ALIBABA_TONGYI_DEEPRESEARCH_30B_A3B_FREE = "alibaba/tongyi-deepresearch-30b-a3b:free", MODEL_FREE_NVIDIA_NEMOTRON_NANO_9B_V2_FREE = "nvidia/nemotron-nano-9b-v2:free", - MODEL_FREE_DEEPSEEK_DEEPSEEK_CHAT_V3_1_FREE = "deepseek/deepseek-chat-v3.1:free", MODEL_FREE_OPENAI_GPT_OSS_120B_FREE = "openai/gpt-oss-120b:free", MODEL_FREE_OPENAI_GPT_OSS_20B_FREE = "openai/gpt-oss-20b:free", MODEL_FREE_Z_AI_GLM_4_5_AIR_FREE = "z-ai/glm-4.5-air:free", @@ -9,49 +18,20 @@ export declare enum E_OPENROUTER_MODEL_FREE { MODEL_FREE_MOONSHOTAI_KIMI_K2_FREE = "moonshotai/kimi-k2:free", MODEL_FREE_COGNITIVECOMPUTATIONS_DOLPHIN_MISTRAL_24B_VENICE_EDITION_FREE = "cognitivecomputations/dolphin-mistral-24b-venice-edition:free", MODEL_FREE_GOOGLE_GEMMA_3N_E2B_IT_FREE = "google/gemma-3n-e2b-it:free", - MODEL_FREE_TENCENT_HUNYUAN_A13B_INSTRUCT_FREE = "tencent/hunyuan-a13b-instruct:free", MODEL_FREE_TNGTECH_DEEPSEEK_R1T2_CHIMERA_FREE = "tngtech/deepseek-r1t2-chimera:free", - MODEL_FREE_MISTRALAI_MISTRAL_SMALL_3_2_24B_INSTRUCT_FREE = "mistralai/mistral-small-3.2-24b-instruct:free", - MODEL_FREE_MOONSHOTAI_KIMI_DEV_72B_FREE = "moonshotai/kimi-dev-72b:free", - MODEL_FREE_DEEPSEEK_DEEPSEEK_R1_0528_QWEN3_8B_FREE = "deepseek/deepseek-r1-0528-qwen3-8b:free", MODEL_FREE_DEEPSEEK_DEEPSEEK_R1_0528_FREE = "deepseek/deepseek-r1-0528:free", - MODEL_FREE_MISTRALAI_DEVSTRAL_SMALL_2505_FREE = "mistralai/devstral-small-2505:free", MODEL_FREE_GOOGLE_GEMMA_3N_E4B_IT_FREE = "google/gemma-3n-e4b-it:free", - MODEL_FREE_META_LLAMA_LLAMA_3_3_8B_INSTRUCT_FREE = "meta-llama/llama-3.3-8b-instruct:free", MODEL_FREE_QWEN_QWEN3_4B_FREE = "qwen/qwen3-4b:free", - MODEL_FREE_QWEN_QWEN3_30B_A3B_FREE = "qwen/qwen3-30b-a3b:free", - MODEL_FREE_QWEN_QWEN3_8B_FREE = "qwen/qwen3-8b:free", - MODEL_FREE_QWEN_QWEN3_14B_FREE = "qwen/qwen3-14b:free", - MODEL_FREE_QWEN_QWEN3_235B_A22B_FREE = "qwen/qwen3-235b-a22b:free", MODEL_FREE_TNGTECH_DEEPSEEK_R1T_CHIMERA_FREE = "tngtech/deepseek-r1t-chimera:free", - MODEL_FREE_MICROSOFT_MAI_DS_R1_FREE = "microsoft/mai-ds-r1:free", - MODEL_FREE_SHISA_AI_SHISA_V2_LLAMA3_3_70B_FREE = "shisa-ai/shisa-v2-llama3.3-70b:free", - MODEL_FREE_ARLIAI_QWQ_32B_ARLIAI_RPR_V1_FREE = "arliai/qwq-32b-arliai-rpr-v1:free", - MODEL_FREE_AGENTICA_ORG_DEEPCODER_14B_PREVIEW_FREE = "agentica-org/deepcoder-14b-preview:free", - MODEL_FREE_MOONSHOTAI_KIMI_VL_A3B_THINKING_FREE = "moonshotai/kimi-vl-a3b-thinking:free", - MODEL_FREE_META_LLAMA_LLAMA_4_MAVERICK_FREE = "meta-llama/llama-4-maverick:free", - MODEL_FREE_META_LLAMA_LLAMA_4_SCOUT_FREE = "meta-llama/llama-4-scout:free", - MODEL_FREE_QWEN_QWEN2_5_VL_32B_INSTRUCT_FREE = "qwen/qwen2.5-vl-32b-instruct:free", - MODEL_FREE_DEEPSEEK_DEEPSEEK_CHAT_V3_0324_FREE = "deepseek/deepseek-chat-v3-0324:free", MODEL_FREE_MISTRALAI_MISTRAL_SMALL_3_1_24B_INSTRUCT_FREE = "mistralai/mistral-small-3.1-24b-instruct:free", MODEL_FREE_GOOGLE_GEMMA_3_4B_IT_FREE = "google/gemma-3-4b-it:free", MODEL_FREE_GOOGLE_GEMMA_3_12B_IT_FREE = "google/gemma-3-12b-it:free", MODEL_FREE_GOOGLE_GEMMA_3_27B_IT_FREE = "google/gemma-3-27b-it:free", - MODEL_FREE_QWEN_QWQ_32B_FREE = "qwen/qwq-32b:free", - MODEL_FREE_NOUSRESEARCH_DEEPHERMES_3_LLAMA_3_8B_PREVIEW_FREE = "nousresearch/deephermes-3-llama-3-8b-preview:free", - MODEL_FREE_COGNITIVECOMPUTATIONS_DOLPHIN3_0_R1_MISTRAL_24B_FREE = "cognitivecomputations/dolphin3.0-r1-mistral-24b:free", - MODEL_FREE_COGNITIVECOMPUTATIONS_DOLPHIN3_0_MISTRAL_24B_FREE = "cognitivecomputations/dolphin3.0-mistral-24b:free", - MODEL_FREE_QWEN_QWEN2_5_VL_72B_INSTRUCT_FREE = "qwen/qwen2.5-vl-72b-instruct:free", - MODEL_FREE_MISTRALAI_MISTRAL_SMALL_24B_INSTRUCT_2501_FREE = "mistralai/mistral-small-24b-instruct-2501:free", - MODEL_FREE_DEEPSEEK_DEEPSEEK_R1_DISTILL_LLAMA_70B_FREE = "deepseek/deepseek-r1-distill-llama-70b:free", - MODEL_FREE_DEEPSEEK_DEEPSEEK_R1_FREE = "deepseek/deepseek-r1:free", MODEL_FREE_GOOGLE_GEMINI_2_0_FLASH_EXP_FREE = "google/gemini-2.0-flash-exp:free", MODEL_FREE_META_LLAMA_LLAMA_3_3_70B_INSTRUCT_FREE = "meta-llama/llama-3.3-70b-instruct:free", - MODEL_FREE_QWEN_QWEN_2_5_CODER_32B_INSTRUCT_FREE = "qwen/qwen-2.5-coder-32b-instruct:free", MODEL_FREE_META_LLAMA_LLAMA_3_2_3B_INSTRUCT_FREE = "meta-llama/llama-3.2-3b-instruct:free", - MODEL_FREE_QWEN_QWEN_2_5_72B_INSTRUCT_FREE = "qwen/qwen-2.5-72b-instruct:free", + MODEL_FREE_QWEN_QWEN_2_5_VL_7B_INSTRUCT_FREE = "qwen/qwen-2.5-vl-7b-instruct:free", + MODEL_FREE_NOUSRESEARCH_HERMES_3_LLAMA_3_1_405B_FREE = "nousresearch/hermes-3-llama-3.1-405b:free", MODEL_FREE_META_LLAMA_LLAMA_3_1_405B_INSTRUCT_FREE = "meta-llama/llama-3.1-405b-instruct:free", - MODEL_FREE_MISTRALAI_MISTRAL_NEMO_FREE = "mistralai/mistral-nemo:free", - MODEL_FREE_GOOGLE_GEMMA_2_9B_IT_FREE = "google/gemma-2-9b-it:free", MODEL_FREE_MISTRALAI_MISTRAL_7B_INSTRUCT_FREE = "mistralai/mistral-7b-instruct:free" } diff --git a/packages/kbot/dist-in/models/cache/openrouter-models-free.js b/packages/kbot/dist-in/models/cache/openrouter-models-free.js index 01da280c..2e7bf57a 100644 --- a/packages/kbot/dist-in/models/cache/openrouter-models-free.js +++ b/packages/kbot/dist-in/models/cache/openrouter-models-free.js @@ -1,8 +1,17 @@ export var E_OPENROUTER_MODEL_FREE; (function (E_OPENROUTER_MODEL_FREE) { - E_OPENROUTER_MODEL_FREE["MODEL_FREE_X_AI_GROK_4_FAST_FREE"] = "x-ai/grok-4-fast:free"; + E_OPENROUTER_MODEL_FREE["MODEL_FREE_ALLENAI_OLMO_3_1_32B_THINK_FREE"] = "allenai/olmo-3.1-32b-think:free"; + E_OPENROUTER_MODEL_FREE["MODEL_FREE_XIAOMI_MIMO_V2_FLASH_FREE"] = "xiaomi/mimo-v2-flash:free"; + E_OPENROUTER_MODEL_FREE["MODEL_FREE_NVIDIA_NEMOTRON_3_NANO_30B_A3B_FREE"] = "nvidia/nemotron-3-nano-30b-a3b:free"; + E_OPENROUTER_MODEL_FREE["MODEL_FREE_MISTRALAI_DEVSTRAL_2512_FREE"] = "mistralai/devstral-2512:free"; + E_OPENROUTER_MODEL_FREE["MODEL_FREE_NEX_AGI_DEEPSEEK_V3_1_NEX_N1_FREE"] = "nex-agi/deepseek-v3.1-nex-n1:free"; + E_OPENROUTER_MODEL_FREE["MODEL_FREE_ARCEE_AI_TRINITY_MINI_FREE"] = "arcee-ai/trinity-mini:free"; + E_OPENROUTER_MODEL_FREE["MODEL_FREE_TNGTECH_TNG_R1T_CHIMERA_FREE"] = "tngtech/tng-r1t-chimera:free"; + E_OPENROUTER_MODEL_FREE["MODEL_FREE_ALLENAI_OLMO_3_32B_THINK_FREE"] = "allenai/olmo-3-32b-think:free"; + E_OPENROUTER_MODEL_FREE["MODEL_FREE_KWAIPILOT_KAT_CODER_PRO_FREE"] = "kwaipilot/kat-coder-pro:free"; + E_OPENROUTER_MODEL_FREE["MODEL_FREE_NVIDIA_NEMOTRON_NANO_12B_V2_VL_FREE"] = "nvidia/nemotron-nano-12b-v2-vl:free"; + E_OPENROUTER_MODEL_FREE["MODEL_FREE_ALIBABA_TONGYI_DEEPRESEARCH_30B_A3B_FREE"] = "alibaba/tongyi-deepresearch-30b-a3b:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_NVIDIA_NEMOTRON_NANO_9B_V2_FREE"] = "nvidia/nemotron-nano-9b-v2:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_DEEPSEEK_DEEPSEEK_CHAT_V3_1_FREE"] = "deepseek/deepseek-chat-v3.1:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_OPENAI_GPT_OSS_120B_FREE"] = "openai/gpt-oss-120b:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_OPENAI_GPT_OSS_20B_FREE"] = "openai/gpt-oss-20b:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_Z_AI_GLM_4_5_AIR_FREE"] = "z-ai/glm-4.5-air:free"; @@ -10,50 +19,21 @@ export var E_OPENROUTER_MODEL_FREE; E_OPENROUTER_MODEL_FREE["MODEL_FREE_MOONSHOTAI_KIMI_K2_FREE"] = "moonshotai/kimi-k2:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_COGNITIVECOMPUTATIONS_DOLPHIN_MISTRAL_24B_VENICE_EDITION_FREE"] = "cognitivecomputations/dolphin-mistral-24b-venice-edition:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_GOOGLE_GEMMA_3N_E2B_IT_FREE"] = "google/gemma-3n-e2b-it:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_TENCENT_HUNYUAN_A13B_INSTRUCT_FREE"] = "tencent/hunyuan-a13b-instruct:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_TNGTECH_DEEPSEEK_R1T2_CHIMERA_FREE"] = "tngtech/deepseek-r1t2-chimera:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_MISTRALAI_MISTRAL_SMALL_3_2_24B_INSTRUCT_FREE"] = "mistralai/mistral-small-3.2-24b-instruct:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_MOONSHOTAI_KIMI_DEV_72B_FREE"] = "moonshotai/kimi-dev-72b:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_DEEPSEEK_DEEPSEEK_R1_0528_QWEN3_8B_FREE"] = "deepseek/deepseek-r1-0528-qwen3-8b:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_DEEPSEEK_DEEPSEEK_R1_0528_FREE"] = "deepseek/deepseek-r1-0528:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_MISTRALAI_DEVSTRAL_SMALL_2505_FREE"] = "mistralai/devstral-small-2505:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_GOOGLE_GEMMA_3N_E4B_IT_FREE"] = "google/gemma-3n-e4b-it:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_META_LLAMA_LLAMA_3_3_8B_INSTRUCT_FREE"] = "meta-llama/llama-3.3-8b-instruct:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_QWEN_QWEN3_4B_FREE"] = "qwen/qwen3-4b:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_QWEN_QWEN3_30B_A3B_FREE"] = "qwen/qwen3-30b-a3b:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_QWEN_QWEN3_8B_FREE"] = "qwen/qwen3-8b:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_QWEN_QWEN3_14B_FREE"] = "qwen/qwen3-14b:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_QWEN_QWEN3_235B_A22B_FREE"] = "qwen/qwen3-235b-a22b:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_TNGTECH_DEEPSEEK_R1T_CHIMERA_FREE"] = "tngtech/deepseek-r1t-chimera:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_MICROSOFT_MAI_DS_R1_FREE"] = "microsoft/mai-ds-r1:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_SHISA_AI_SHISA_V2_LLAMA3_3_70B_FREE"] = "shisa-ai/shisa-v2-llama3.3-70b:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_ARLIAI_QWQ_32B_ARLIAI_RPR_V1_FREE"] = "arliai/qwq-32b-arliai-rpr-v1:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_AGENTICA_ORG_DEEPCODER_14B_PREVIEW_FREE"] = "agentica-org/deepcoder-14b-preview:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_MOONSHOTAI_KIMI_VL_A3B_THINKING_FREE"] = "moonshotai/kimi-vl-a3b-thinking:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_META_LLAMA_LLAMA_4_MAVERICK_FREE"] = "meta-llama/llama-4-maverick:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_META_LLAMA_LLAMA_4_SCOUT_FREE"] = "meta-llama/llama-4-scout:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_QWEN_QWEN2_5_VL_32B_INSTRUCT_FREE"] = "qwen/qwen2.5-vl-32b-instruct:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_DEEPSEEK_DEEPSEEK_CHAT_V3_0324_FREE"] = "deepseek/deepseek-chat-v3-0324:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_MISTRALAI_MISTRAL_SMALL_3_1_24B_INSTRUCT_FREE"] = "mistralai/mistral-small-3.1-24b-instruct:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_GOOGLE_GEMMA_3_4B_IT_FREE"] = "google/gemma-3-4b-it:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_GOOGLE_GEMMA_3_12B_IT_FREE"] = "google/gemma-3-12b-it:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_GOOGLE_GEMMA_3_27B_IT_FREE"] = "google/gemma-3-27b-it:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_QWEN_QWQ_32B_FREE"] = "qwen/qwq-32b:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_NOUSRESEARCH_DEEPHERMES_3_LLAMA_3_8B_PREVIEW_FREE"] = "nousresearch/deephermes-3-llama-3-8b-preview:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_COGNITIVECOMPUTATIONS_DOLPHIN3_0_R1_MISTRAL_24B_FREE"] = "cognitivecomputations/dolphin3.0-r1-mistral-24b:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_COGNITIVECOMPUTATIONS_DOLPHIN3_0_MISTRAL_24B_FREE"] = "cognitivecomputations/dolphin3.0-mistral-24b:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_QWEN_QWEN2_5_VL_72B_INSTRUCT_FREE"] = "qwen/qwen2.5-vl-72b-instruct:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_MISTRALAI_MISTRAL_SMALL_24B_INSTRUCT_2501_FREE"] = "mistralai/mistral-small-24b-instruct-2501:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_DEEPSEEK_DEEPSEEK_R1_DISTILL_LLAMA_70B_FREE"] = "deepseek/deepseek-r1-distill-llama-70b:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_DEEPSEEK_DEEPSEEK_R1_FREE"] = "deepseek/deepseek-r1:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_GOOGLE_GEMINI_2_0_FLASH_EXP_FREE"] = "google/gemini-2.0-flash-exp:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_META_LLAMA_LLAMA_3_3_70B_INSTRUCT_FREE"] = "meta-llama/llama-3.3-70b-instruct:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_QWEN_QWEN_2_5_CODER_32B_INSTRUCT_FREE"] = "qwen/qwen-2.5-coder-32b-instruct:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_META_LLAMA_LLAMA_3_2_3B_INSTRUCT_FREE"] = "meta-llama/llama-3.2-3b-instruct:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_QWEN_QWEN_2_5_72B_INSTRUCT_FREE"] = "qwen/qwen-2.5-72b-instruct:free"; + E_OPENROUTER_MODEL_FREE["MODEL_FREE_QWEN_QWEN_2_5_VL_7B_INSTRUCT_FREE"] = "qwen/qwen-2.5-vl-7b-instruct:free"; + E_OPENROUTER_MODEL_FREE["MODEL_FREE_NOUSRESEARCH_HERMES_3_LLAMA_3_1_405B_FREE"] = "nousresearch/hermes-3-llama-3.1-405b:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_META_LLAMA_LLAMA_3_1_405B_INSTRUCT_FREE"] = "meta-llama/llama-3.1-405b-instruct:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_MISTRALAI_MISTRAL_NEMO_FREE"] = "mistralai/mistral-nemo:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_GOOGLE_GEMMA_2_9B_IT_FREE"] = "google/gemma-2-9b-it:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_MISTRALAI_MISTRAL_7B_INSTRUCT_FREE"] = "mistralai/mistral-7b-instruct:free"; })(E_OPENROUTER_MODEL_FREE || (E_OPENROUTER_MODEL_FREE = {})); -//# 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\ No newline at end of file diff --git a/packages/kbot/dist-in/models/cache/openrouter-models.d.ts b/packages/kbot/dist-in/models/cache/openrouter-models.d.ts index 5f9eab3d..a5243425 100644 --- a/packages/kbot/dist-in/models/cache/openrouter-models.d.ts +++ b/packages/kbot/dist-in/models/cache/openrouter-models.d.ts @@ -1,9 +1,95 @@ export declare enum E_OPENROUTER_MODEL { - MODEL_X_AI_GROK_4_FAST_FREE = "x-ai/grok-4-fast:free", + MODEL_BYTEDANCE_SEED_SEED_1_6_FLASH = "bytedance-seed/seed-1.6-flash", + MODEL_BYTEDANCE_SEED_SEED_1_6 = "bytedance-seed/seed-1.6", + MODEL_MINIMAX_MINIMAX_M2_1 = "minimax/minimax-m2.1", + MODEL_Z_AI_GLM_4_7 = "z-ai/glm-4.7", + MODEL_GOOGLE_GEMINI_3_FLASH_PREVIEW = "google/gemini-3-flash-preview", + MODEL_MISTRALAI_MISTRAL_SMALL_CREATIVE = "mistralai/mistral-small-creative", + MODEL_ALLENAI_OLMO_3_1_32B_THINK_FREE = "allenai/olmo-3.1-32b-think:free", + MODEL_XIAOMI_MIMO_V2_FLASH_FREE = "xiaomi/mimo-v2-flash:free", + MODEL_NVIDIA_NEMOTRON_3_NANO_30B_A3B_FREE = "nvidia/nemotron-3-nano-30b-a3b:free", + MODEL_NVIDIA_NEMOTRON_3_NANO_30B_A3B = "nvidia/nemotron-3-nano-30b-a3b", + MODEL_OPENAI_GPT_5_2_CHAT = "openai/gpt-5.2-chat", + MODEL_OPENAI_GPT_5_2_PRO = "openai/gpt-5.2-pro", + MODEL_OPENAI_GPT_5_2 = "openai/gpt-5.2", + MODEL_MISTRALAI_DEVSTRAL_2512_FREE = "mistralai/devstral-2512:free", + MODEL_MISTRALAI_DEVSTRAL_2512 = "mistralai/devstral-2512", + MODEL_RELACE_RELACE_SEARCH = "relace/relace-search", + MODEL_Z_AI_GLM_4_6V = "z-ai/glm-4.6v", + MODEL_NEX_AGI_DEEPSEEK_V3_1_NEX_N1_FREE = "nex-agi/deepseek-v3.1-nex-n1:free", + MODEL_ESSENTIALAI_RNJ_1_INSTRUCT = "essentialai/rnj-1-instruct", + MODEL_OPENROUTER_BODYBUILDER = "openrouter/bodybuilder", + MODEL_OPENAI_GPT_5_1_CODEX_MAX = "openai/gpt-5.1-codex-max", + MODEL_AMAZON_NOVA_2_LITE_V1 = "amazon/nova-2-lite-v1", + MODEL_MISTRALAI_MINISTRAL_14B_2512 = "mistralai/ministral-14b-2512", + MODEL_MISTRALAI_MINISTRAL_8B_2512 = "mistralai/ministral-8b-2512", + MODEL_MISTRALAI_MINISTRAL_3B_2512 = "mistralai/ministral-3b-2512", + MODEL_MISTRALAI_MISTRAL_LARGE_2512 = "mistralai/mistral-large-2512", + MODEL_ARCEE_AI_TRINITY_MINI_FREE = "arcee-ai/trinity-mini:free", + MODEL_ARCEE_AI_TRINITY_MINI = "arcee-ai/trinity-mini", + MODEL_DEEPSEEK_DEEPSEEK_V3_2_SPECIALE = "deepseek/deepseek-v3.2-speciale", + MODEL_DEEPSEEK_DEEPSEEK_V3_2 = "deepseek/deepseek-v3.2", + MODEL_PRIME_INTELLECT_INTELLECT_3 = "prime-intellect/intellect-3", + MODEL_TNGTECH_TNG_R1T_CHIMERA_FREE = "tngtech/tng-r1t-chimera:free", + MODEL_TNGTECH_TNG_R1T_CHIMERA = "tngtech/tng-r1t-chimera", + MODEL_ANTHROPIC_CLAUDE_OPUS_4_5 = "anthropic/claude-opus-4.5", + MODEL_ALLENAI_OLMO_3_32B_THINK_FREE = "allenai/olmo-3-32b-think:free", + MODEL_ALLENAI_OLMO_3_7B_INSTRUCT = "allenai/olmo-3-7b-instruct", + MODEL_ALLENAI_OLMO_3_7B_THINK = "allenai/olmo-3-7b-think", + MODEL_GOOGLE_GEMINI_3_PRO_IMAGE_PREVIEW = "google/gemini-3-pro-image-preview", + MODEL_X_AI_GROK_4_1_FAST = "x-ai/grok-4.1-fast", + MODEL_GOOGLE_GEMINI_3_PRO_PREVIEW = "google/gemini-3-pro-preview", + MODEL_DEEPCOGITO_COGITO_V2_1_671B = "deepcogito/cogito-v2.1-671b", + MODEL_OPENAI_GPT_5_1 = "openai/gpt-5.1", + MODEL_OPENAI_GPT_5_1_CHAT = "openai/gpt-5.1-chat", + MODEL_OPENAI_GPT_5_1_CODEX = "openai/gpt-5.1-codex", + MODEL_OPENAI_GPT_5_1_CODEX_MINI = "openai/gpt-5.1-codex-mini", + MODEL_KWAIPILOT_KAT_CODER_PRO_FREE = "kwaipilot/kat-coder-pro:free", + MODEL_MOONSHOTAI_KIMI_K2_THINKING = "moonshotai/kimi-k2-thinking", + MODEL_AMAZON_NOVA_PREMIER_V1 = "amazon/nova-premier-v1", + MODEL_PERPLEXITY_SONAR_PRO_SEARCH = "perplexity/sonar-pro-search", + MODEL_MISTRALAI_VOXTRAL_SMALL_24B_2507 = "mistralai/voxtral-small-24b-2507", + MODEL_OPENAI_GPT_OSS_SAFEGUARD_20B = "openai/gpt-oss-safeguard-20b", + MODEL_NVIDIA_NEMOTRON_NANO_12B_V2_VL_FREE = "nvidia/nemotron-nano-12b-v2-vl:free", + MODEL_NVIDIA_NEMOTRON_NANO_12B_V2_VL = "nvidia/nemotron-nano-12b-v2-vl", + MODEL_MINIMAX_MINIMAX_M2 = "minimax/minimax-m2", + MODEL_QWEN_QWEN3_VL_32B_INSTRUCT = "qwen/qwen3-vl-32b-instruct", + MODEL_LIQUID_LFM2_8B_A1B = "liquid/lfm2-8b-a1b", + MODEL_LIQUID_LFM_2_2_6B = "liquid/lfm-2.2-6b", + MODEL_IBM_GRANITE_GRANITE_4_0_H_MICRO = "ibm-granite/granite-4.0-h-micro", + MODEL_DEEPCOGITO_COGITO_V2_PREVIEW_LLAMA_405B = "deepcogito/cogito-v2-preview-llama-405b", + MODEL_OPENAI_GPT_5_IMAGE_MINI = "openai/gpt-5-image-mini", + MODEL_ANTHROPIC_CLAUDE_HAIKU_4_5 = "anthropic/claude-haiku-4.5", + MODEL_QWEN_QWEN3_VL_8B_THINKING = "qwen/qwen3-vl-8b-thinking", + MODEL_QWEN_QWEN3_VL_8B_INSTRUCT = "qwen/qwen3-vl-8b-instruct", + MODEL_OPENAI_GPT_5_IMAGE = "openai/gpt-5-image", + MODEL_OPENAI_O3_DEEP_RESEARCH = "openai/o3-deep-research", + MODEL_OPENAI_O4_MINI_DEEP_RESEARCH = "openai/o4-mini-deep-research", + MODEL_NVIDIA_LLAMA_3_3_NEMOTRON_SUPER_49B_V1_5 = "nvidia/llama-3.3-nemotron-super-49b-v1.5", + MODEL_BAIDU_ERNIE_4_5_21B_A3B_THINKING = "baidu/ernie-4.5-21b-a3b-thinking", + MODEL_GOOGLE_GEMINI_2_5_FLASH_IMAGE = "google/gemini-2.5-flash-image", + MODEL_QWEN_QWEN3_VL_30B_A3B_THINKING = "qwen/qwen3-vl-30b-a3b-thinking", + MODEL_QWEN_QWEN3_VL_30B_A3B_INSTRUCT = "qwen/qwen3-vl-30b-a3b-instruct", + MODEL_OPENAI_GPT_5_PRO = "openai/gpt-5-pro", + MODEL_Z_AI_GLM_4_6 = "z-ai/glm-4.6", + MODEL_Z_AI_GLM_4_6_EXACTO = "z-ai/glm-4.6:exacto", + MODEL_ANTHROPIC_CLAUDE_SONNET_4_5 = "anthropic/claude-sonnet-4.5", + MODEL_DEEPSEEK_DEEPSEEK_V3_2_EXP = "deepseek/deepseek-v3.2-exp", + MODEL_THEDRUMMER_CYDONIA_24B_V4_1 = "thedrummer/cydonia-24b-v4.1", + MODEL_RELACE_RELACE_APPLY_3 = "relace/relace-apply-3", + MODEL_GOOGLE_GEMINI_2_5_FLASH_PREVIEW_09_2025 = "google/gemini-2.5-flash-preview-09-2025", + MODEL_GOOGLE_GEMINI_2_5_FLASH_LITE_PREVIEW_09_2025 = "google/gemini-2.5-flash-lite-preview-09-2025", + MODEL_QWEN_QWEN3_VL_235B_A22B_THINKING = "qwen/qwen3-vl-235b-a22b-thinking", + MODEL_QWEN_QWEN3_VL_235B_A22B_INSTRUCT = "qwen/qwen3-vl-235b-a22b-instruct", + MODEL_QWEN_QWEN3_MAX = "qwen/qwen3-max", + MODEL_QWEN_QWEN3_CODER_PLUS = "qwen/qwen3-coder-plus", + MODEL_OPENAI_GPT_5_CODEX = "openai/gpt-5-codex", + MODEL_DEEPSEEK_DEEPSEEK_V3_1_TERMINUS_EXACTO = "deepseek/deepseek-v3.1-terminus:exacto", + MODEL_DEEPSEEK_DEEPSEEK_V3_1_TERMINUS = "deepseek/deepseek-v3.1-terminus", + MODEL_X_AI_GROK_4_FAST = "x-ai/grok-4-fast", + MODEL_ALIBABA_TONGYI_DEEPRESEARCH_30B_A3B_FREE = "alibaba/tongyi-deepresearch-30b-a3b:free", MODEL_ALIBABA_TONGYI_DEEPRESEARCH_30B_A3B = "alibaba/tongyi-deepresearch-30b-a3b", MODEL_QWEN_QWEN3_CODER_FLASH = "qwen/qwen3-coder-flash", - MODEL_QWEN_QWEN3_CODER_PLUS = "qwen/qwen3-coder-plus", - MODEL_ARCEE_AI_AFM_4_5B = "arcee-ai/afm-4.5b", MODEL_OPENGVLAB_INTERNVL3_78B = "opengvlab/internvl3-78b", MODEL_QWEN_QWEN3_NEXT_80B_A3B_THINKING = "qwen/qwen3-next-80b-a3b-thinking", MODEL_QWEN_QWEN3_NEXT_80B_A3B_INSTRUCT = "qwen/qwen3-next-80b-a3b-instruct", @@ -12,20 +98,17 @@ export declare enum E_OPENROUTER_MODEL { MODEL_QWEN_QWEN_PLUS_2025_07_28_THINKING = "qwen/qwen-plus-2025-07-28:thinking", MODEL_NVIDIA_NEMOTRON_NANO_9B_V2_FREE = "nvidia/nemotron-nano-9b-v2:free", MODEL_NVIDIA_NEMOTRON_NANO_9B_V2 = "nvidia/nemotron-nano-9b-v2", - MODEL_QWEN_QWEN3_MAX = "qwen/qwen3-max", MODEL_MOONSHOTAI_KIMI_K2_0905 = "moonshotai/kimi-k2-0905", - MODEL_BYTEDANCE_SEED_OSS_36B_INSTRUCT = "bytedance/seed-oss-36b-instruct", + MODEL_MOONSHOTAI_KIMI_K2_0905_EXACTO = "moonshotai/kimi-k2-0905:exacto", + MODEL_DEEPCOGITO_COGITO_V2_PREVIEW_LLAMA_70B = "deepcogito/cogito-v2-preview-llama-70b", MODEL_DEEPCOGITO_COGITO_V2_PREVIEW_LLAMA_109B_MOE = "deepcogito/cogito-v2-preview-llama-109b-moe", - MODEL_DEEPCOGITO_COGITO_V2_PREVIEW_DEEPSEEK_671B = "deepcogito/cogito-v2-preview-deepseek-671b", MODEL_STEPFUN_AI_STEP3 = "stepfun-ai/step3", MODEL_QWEN_QWEN3_30B_A3B_THINKING_2507 = "qwen/qwen3-30b-a3b-thinking-2507", MODEL_X_AI_GROK_CODE_FAST_1 = "x-ai/grok-code-fast-1", MODEL_NOUSRESEARCH_HERMES_4_70B = "nousresearch/hermes-4-70b", MODEL_NOUSRESEARCH_HERMES_4_405B = "nousresearch/hermes-4-405b", MODEL_GOOGLE_GEMINI_2_5_FLASH_IMAGE_PREVIEW = "google/gemini-2.5-flash-image-preview", - MODEL_DEEPSEEK_DEEPSEEK_CHAT_V3_1_FREE = "deepseek/deepseek-chat-v3.1:free", MODEL_DEEPSEEK_DEEPSEEK_CHAT_V3_1 = "deepseek/deepseek-chat-v3.1", - MODEL_DEEPSEEK_DEEPSEEK_V3_1_BASE = "deepseek/deepseek-v3.1-base", MODEL_OPENAI_GPT_4O_AUDIO_PREVIEW = "openai/gpt-4o-audio-preview", MODEL_MISTRALAI_MISTRAL_MEDIUM_3_1 = "mistralai/mistral-medium-3.1", MODEL_BAIDU_ERNIE_4_5_21B_A3B = "baidu/ernie-4.5-21b-a3b", @@ -39,6 +122,7 @@ export declare enum E_OPENROUTER_MODEL { MODEL_OPENAI_GPT_5_NANO = "openai/gpt-5-nano", MODEL_OPENAI_GPT_OSS_120B_FREE = "openai/gpt-oss-120b:free", MODEL_OPENAI_GPT_OSS_120B = "openai/gpt-oss-120b", + MODEL_OPENAI_GPT_OSS_120B_EXACTO = "openai/gpt-oss-120b:exacto", MODEL_OPENAI_GPT_OSS_20B_FREE = "openai/gpt-oss-20b:free", MODEL_OPENAI_GPT_OSS_20B = "openai/gpt-oss-20b", MODEL_ANTHROPIC_CLAUDE_OPUS_4_1 = "anthropic/claude-opus-4.1", @@ -52,6 +136,7 @@ export declare enum E_OPENROUTER_MODEL { MODEL_Z_AI_GLM_4_32B = "z-ai/glm-4-32b", MODEL_QWEN_QWEN3_CODER_FREE = "qwen/qwen3-coder:free", MODEL_QWEN_QWEN3_CODER = "qwen/qwen3-coder", + MODEL_QWEN_QWEN3_CODER_EXACTO = "qwen/qwen3-coder:exacto", MODEL_BYTEDANCE_UI_TARS_1_5_7B = "bytedance/ui-tars-1.5-7b", MODEL_GOOGLE_GEMINI_2_5_FLASH_LITE = "google/gemini-2.5-flash-lite", MODEL_QWEN_QWEN3_235B_A22B_2507 = "qwen/qwen3-235b-a22b-2507", @@ -64,42 +149,32 @@ export declare enum E_OPENROUTER_MODEL { MODEL_COGNITIVECOMPUTATIONS_DOLPHIN_MISTRAL_24B_VENICE_EDITION_FREE = "cognitivecomputations/dolphin-mistral-24b-venice-edition:free", MODEL_X_AI_GROK_4 = "x-ai/grok-4", MODEL_GOOGLE_GEMMA_3N_E2B_IT_FREE = "google/gemma-3n-e2b-it:free", - MODEL_TENCENT_HUNYUAN_A13B_INSTRUCT_FREE = "tencent/hunyuan-a13b-instruct:free", MODEL_TENCENT_HUNYUAN_A13B_INSTRUCT = "tencent/hunyuan-a13b-instruct", MODEL_TNGTECH_DEEPSEEK_R1T2_CHIMERA_FREE = "tngtech/deepseek-r1t2-chimera:free", + MODEL_TNGTECH_DEEPSEEK_R1T2_CHIMERA = "tngtech/deepseek-r1t2-chimera", MODEL_MORPH_MORPH_V3_LARGE = "morph/morph-v3-large", MODEL_MORPH_MORPH_V3_FAST = "morph/morph-v3-fast", MODEL_BAIDU_ERNIE_4_5_VL_424B_A47B = "baidu/ernie-4.5-vl-424b-a47b", MODEL_BAIDU_ERNIE_4_5_300B_A47B = "baidu/ernie-4.5-300b-a47b", - MODEL_THEDRUMMER_ANUBIS_70B_V1_1 = "thedrummer/anubis-70b-v1.1", MODEL_INCEPTION_MERCURY = "inception/mercury", - MODEL_MISTRALAI_MISTRAL_SMALL_3_2_24B_INSTRUCT_FREE = "mistralai/mistral-small-3.2-24b-instruct:free", MODEL_MISTRALAI_MISTRAL_SMALL_3_2_24B_INSTRUCT = "mistralai/mistral-small-3.2-24b-instruct", MODEL_MINIMAX_MINIMAX_M1 = "minimax/minimax-m1", - MODEL_GOOGLE_GEMINI_2_5_FLASH_LITE_PREVIEW_06_17 = "google/gemini-2.5-flash-lite-preview-06-17", MODEL_GOOGLE_GEMINI_2_5_FLASH = "google/gemini-2.5-flash", MODEL_GOOGLE_GEMINI_2_5_PRO = "google/gemini-2.5-pro", - MODEL_MOONSHOTAI_KIMI_DEV_72B_FREE = "moonshotai/kimi-dev-72b:free", MODEL_MOONSHOTAI_KIMI_DEV_72B = "moonshotai/kimi-dev-72b", MODEL_OPENAI_O3_PRO = "openai/o3-pro", MODEL_X_AI_GROK_3_MINI = "x-ai/grok-3-mini", MODEL_X_AI_GROK_3 = "x-ai/grok-3", - MODEL_MISTRALAI_MAGISTRAL_SMALL_2506 = "mistralai/magistral-small-2506", - MODEL_MISTRALAI_MAGISTRAL_MEDIUM_2506 = "mistralai/magistral-medium-2506", - MODEL_MISTRALAI_MAGISTRAL_MEDIUM_2506_THINKING = "mistralai/magistral-medium-2506:thinking", MODEL_GOOGLE_GEMINI_2_5_PRO_PREVIEW = "google/gemini-2.5-pro-preview", - MODEL_DEEPSEEK_DEEPSEEK_R1_0528_QWEN3_8B_FREE = "deepseek/deepseek-r1-0528-qwen3-8b:free", MODEL_DEEPSEEK_DEEPSEEK_R1_0528_QWEN3_8B = "deepseek/deepseek-r1-0528-qwen3-8b", MODEL_DEEPSEEK_DEEPSEEK_R1_0528_FREE = "deepseek/deepseek-r1-0528:free", MODEL_DEEPSEEK_DEEPSEEK_R1_0528 = "deepseek/deepseek-r1-0528", MODEL_ANTHROPIC_CLAUDE_OPUS_4 = "anthropic/claude-opus-4", MODEL_ANTHROPIC_CLAUDE_SONNET_4 = "anthropic/claude-sonnet-4", - MODEL_MISTRALAI_DEVSTRAL_SMALL_2505_FREE = "mistralai/devstral-small-2505:free", MODEL_MISTRALAI_DEVSTRAL_SMALL_2505 = "mistralai/devstral-small-2505", MODEL_GOOGLE_GEMMA_3N_E4B_IT_FREE = "google/gemma-3n-e4b-it:free", MODEL_GOOGLE_GEMMA_3N_E4B_IT = "google/gemma-3n-e4b-it", MODEL_OPENAI_CODEX_MINI = "openai/codex-mini", - MODEL_META_LLAMA_LLAMA_3_3_8B_INSTRUCT_FREE = "meta-llama/llama-3.3-8b-instruct:free", MODEL_NOUSRESEARCH_DEEPHERMES_3_MISTRAL_24B_PREVIEW = "nousresearch/deephermes-3-mistral-24b-preview", MODEL_MISTRALAI_MISTRAL_MEDIUM_3 = "mistralai/mistral-medium-3", MODEL_GOOGLE_GEMINI_2_5_PRO_PREVIEW_05_06 = "google/gemini-2.5-pro-preview-05-06", @@ -112,47 +187,29 @@ export declare enum E_OPENROUTER_MODEL { MODEL_QWEN_QWEN3_4B_FREE = "qwen/qwen3-4b:free", MODEL_DEEPSEEK_DEEPSEEK_PROVER_V2 = "deepseek/deepseek-prover-v2", MODEL_META_LLAMA_LLAMA_GUARD_4_12B = "meta-llama/llama-guard-4-12b", - MODEL_QWEN_QWEN3_30B_A3B_FREE = "qwen/qwen3-30b-a3b:free", MODEL_QWEN_QWEN3_30B_A3B = "qwen/qwen3-30b-a3b", - MODEL_QWEN_QWEN3_8B_FREE = "qwen/qwen3-8b:free", MODEL_QWEN_QWEN3_8B = "qwen/qwen3-8b", - MODEL_QWEN_QWEN3_14B_FREE = "qwen/qwen3-14b:free", MODEL_QWEN_QWEN3_14B = "qwen/qwen3-14b", MODEL_QWEN_QWEN3_32B = "qwen/qwen3-32b", - MODEL_QWEN_QWEN3_235B_A22B_FREE = "qwen/qwen3-235b-a22b:free", MODEL_QWEN_QWEN3_235B_A22B = "qwen/qwen3-235b-a22b", MODEL_TNGTECH_DEEPSEEK_R1T_CHIMERA_FREE = "tngtech/deepseek-r1t-chimera:free", MODEL_TNGTECH_DEEPSEEK_R1T_CHIMERA = "tngtech/deepseek-r1t-chimera", - MODEL_MICROSOFT_MAI_DS_R1_FREE = "microsoft/mai-ds-r1:free", - MODEL_MICROSOFT_MAI_DS_R1 = "microsoft/mai-ds-r1", - MODEL_THUDM_GLM_Z1_32B = "thudm/glm-z1-32b", MODEL_OPENAI_O4_MINI_HIGH = "openai/o4-mini-high", MODEL_OPENAI_O3 = "openai/o3", MODEL_OPENAI_O4_MINI = "openai/o4-mini", - MODEL_SHISA_AI_SHISA_V2_LLAMA3_3_70B_FREE = "shisa-ai/shisa-v2-llama3.3-70b:free", - MODEL_SHISA_AI_SHISA_V2_LLAMA3_3_70B = "shisa-ai/shisa-v2-llama3.3-70b", + MODEL_QWEN_QWEN2_5_CODER_7B_INSTRUCT = "qwen/qwen2.5-coder-7b-instruct", MODEL_OPENAI_GPT_4_1 = "openai/gpt-4.1", MODEL_OPENAI_GPT_4_1_MINI = "openai/gpt-4.1-mini", MODEL_OPENAI_GPT_4_1_NANO = "openai/gpt-4.1-nano", MODEL_ELEUTHERAI_LLEMMA_7B = "eleutherai/llemma_7b", MODEL_ALFREDPROS_CODELLAMA_7B_INSTRUCT_SOLIDITY = "alfredpros/codellama-7b-instruct-solidity", - MODEL_ARLIAI_QWQ_32B_ARLIAI_RPR_V1_FREE = "arliai/qwq-32b-arliai-rpr-v1:free", MODEL_ARLIAI_QWQ_32B_ARLIAI_RPR_V1 = "arliai/qwq-32b-arliai-rpr-v1", - MODEL_AGENTICA_ORG_DEEPCODER_14B_PREVIEW_FREE = "agentica-org/deepcoder-14b-preview:free", - MODEL_AGENTICA_ORG_DEEPCODER_14B_PREVIEW = "agentica-org/deepcoder-14b-preview", - MODEL_MOONSHOTAI_KIMI_VL_A3B_THINKING_FREE = "moonshotai/kimi-vl-a3b-thinking:free", - MODEL_MOONSHOTAI_KIMI_VL_A3B_THINKING = "moonshotai/kimi-vl-a3b-thinking", MODEL_X_AI_GROK_3_MINI_BETA = "x-ai/grok-3-mini-beta", MODEL_X_AI_GROK_3_BETA = "x-ai/grok-3-beta", MODEL_NVIDIA_LLAMA_3_1_NEMOTRON_ULTRA_253B_V1 = "nvidia/llama-3.1-nemotron-ultra-253b-v1", - MODEL_META_LLAMA_LLAMA_4_MAVERICK_FREE = "meta-llama/llama-4-maverick:free", MODEL_META_LLAMA_LLAMA_4_MAVERICK = "meta-llama/llama-4-maverick", - MODEL_META_LLAMA_LLAMA_4_SCOUT_FREE = "meta-llama/llama-4-scout:free", MODEL_META_LLAMA_LLAMA_4_SCOUT = "meta-llama/llama-4-scout", - MODEL_ALLENAI_MOLMO_7B_D = "allenai/molmo-7b-d", - MODEL_QWEN_QWEN2_5_VL_32B_INSTRUCT_FREE = "qwen/qwen2.5-vl-32b-instruct:free", MODEL_QWEN_QWEN2_5_VL_32B_INSTRUCT = "qwen/qwen2.5-vl-32b-instruct", - MODEL_DEEPSEEK_DEEPSEEK_CHAT_V3_0324_FREE = "deepseek/deepseek-chat-v3-0324:free", MODEL_DEEPSEEK_DEEPSEEK_CHAT_V3_0324 = "deepseek/deepseek-chat-v3-0324", MODEL_OPENAI_O1_PRO = "openai/o1-pro", MODEL_MISTRALAI_MISTRAL_SMALL_3_1_24B_INSTRUCT_FREE = "mistralai/mistral-small-3.1-24b-instruct:free", @@ -167,27 +224,18 @@ export declare enum E_OPENROUTER_MODEL { MODEL_OPENAI_GPT_4O_SEARCH_PREVIEW = "openai/gpt-4o-search-preview", MODEL_GOOGLE_GEMMA_3_27B_IT_FREE = "google/gemma-3-27b-it:free", MODEL_GOOGLE_GEMMA_3_27B_IT = "google/gemma-3-27b-it", - MODEL_THEDRUMMER_ANUBIS_PRO_105B_V1 = "thedrummer/anubis-pro-105b-v1", MODEL_THEDRUMMER_SKYFALL_36B_V2 = "thedrummer/skyfall-36b-v2", MODEL_MICROSOFT_PHI_4_MULTIMODAL_INSTRUCT = "microsoft/phi-4-multimodal-instruct", MODEL_PERPLEXITY_SONAR_REASONING_PRO = "perplexity/sonar-reasoning-pro", MODEL_PERPLEXITY_SONAR_PRO = "perplexity/sonar-pro", MODEL_PERPLEXITY_SONAR_DEEP_RESEARCH = "perplexity/sonar-deep-research", - MODEL_QWEN_QWQ_32B_FREE = "qwen/qwq-32b:free", MODEL_QWEN_QWQ_32B = "qwen/qwq-32b", - MODEL_NOUSRESEARCH_DEEPHERMES_3_LLAMA_3_8B_PREVIEW_FREE = "nousresearch/deephermes-3-llama-3-8b-preview:free", MODEL_GOOGLE_GEMINI_2_0_FLASH_LITE_001 = "google/gemini-2.0-flash-lite-001", - MODEL_ANTHROPIC_CLAUDE_3_7_SONNET = "anthropic/claude-3.7-sonnet", MODEL_ANTHROPIC_CLAUDE_3_7_SONNET_THINKING = "anthropic/claude-3.7-sonnet:thinking", - MODEL_PERPLEXITY_R1_1776 = "perplexity/r1-1776", + MODEL_ANTHROPIC_CLAUDE_3_7_SONNET = "anthropic/claude-3.7-sonnet", MODEL_MISTRALAI_MISTRAL_SABA = "mistralai/mistral-saba", - MODEL_COGNITIVECOMPUTATIONS_DOLPHIN3_0_R1_MISTRAL_24B_FREE = "cognitivecomputations/dolphin3.0-r1-mistral-24b:free", - MODEL_COGNITIVECOMPUTATIONS_DOLPHIN3_0_R1_MISTRAL_24B = "cognitivecomputations/dolphin3.0-r1-mistral-24b", - MODEL_COGNITIVECOMPUTATIONS_DOLPHIN3_0_MISTRAL_24B_FREE = "cognitivecomputations/dolphin3.0-mistral-24b:free", - MODEL_COGNITIVECOMPUTATIONS_DOLPHIN3_0_MISTRAL_24B = "cognitivecomputations/dolphin3.0-mistral-24b", MODEL_META_LLAMA_LLAMA_GUARD_3_8B = "meta-llama/llama-guard-3-8b", MODEL_OPENAI_O3_MINI_HIGH = "openai/o3-mini-high", - MODEL_DEEPSEEK_DEEPSEEK_R1_DISTILL_LLAMA_8B = "deepseek/deepseek-r1-distill-llama-8b", MODEL_GOOGLE_GEMINI_2_0_FLASH_001 = "google/gemini-2.0-flash-001", MODEL_QWEN_QWEN_VL_PLUS = "qwen/qwen-vl-plus", MODEL_AION_LABS_AION_1_0 = "aion-labs/aion-1.0", @@ -195,26 +243,20 @@ export declare enum E_OPENROUTER_MODEL { MODEL_AION_LABS_AION_RP_LLAMA_3_1_8B = "aion-labs/aion-rp-llama-3.1-8b", MODEL_QWEN_QWEN_VL_MAX = "qwen/qwen-vl-max", MODEL_QWEN_QWEN_TURBO = "qwen/qwen-turbo", - MODEL_QWEN_QWEN2_5_VL_72B_INSTRUCT_FREE = "qwen/qwen2.5-vl-72b-instruct:free", MODEL_QWEN_QWEN2_5_VL_72B_INSTRUCT = "qwen/qwen2.5-vl-72b-instruct", MODEL_QWEN_QWEN_PLUS = "qwen/qwen-plus", MODEL_QWEN_QWEN_MAX = "qwen/qwen-max", MODEL_OPENAI_O3_MINI = "openai/o3-mini", - MODEL_MISTRALAI_MISTRAL_SMALL_24B_INSTRUCT_2501_FREE = "mistralai/mistral-small-24b-instruct-2501:free", MODEL_MISTRALAI_MISTRAL_SMALL_24B_INSTRUCT_2501 = "mistralai/mistral-small-24b-instruct-2501", MODEL_DEEPSEEK_DEEPSEEK_R1_DISTILL_QWEN_32B = "deepseek/deepseek-r1-distill-qwen-32b", MODEL_DEEPSEEK_DEEPSEEK_R1_DISTILL_QWEN_14B = "deepseek/deepseek-r1-distill-qwen-14b", MODEL_PERPLEXITY_SONAR_REASONING = "perplexity/sonar-reasoning", MODEL_PERPLEXITY_SONAR = "perplexity/sonar", - MODEL_LIQUID_LFM_7B = "liquid/lfm-7b", - MODEL_LIQUID_LFM_3B = "liquid/lfm-3b", - MODEL_DEEPSEEK_DEEPSEEK_R1_DISTILL_LLAMA_70B_FREE = "deepseek/deepseek-r1-distill-llama-70b:free", MODEL_DEEPSEEK_DEEPSEEK_R1_DISTILL_LLAMA_70B = "deepseek/deepseek-r1-distill-llama-70b", - MODEL_DEEPSEEK_DEEPSEEK_R1_FREE = "deepseek/deepseek-r1:free", MODEL_DEEPSEEK_DEEPSEEK_R1 = "deepseek/deepseek-r1", MODEL_MINIMAX_MINIMAX_01 = "minimax/minimax-01", - MODEL_MISTRALAI_CODESTRAL_2501 = "mistralai/codestral-2501", MODEL_MICROSOFT_PHI_4 = "microsoft/phi-4", + MODEL_SAO10K_L3_1_70B_HANAMI_X1 = "sao10k/l3.1-70b-hanami-x1", MODEL_DEEPSEEK_DEEPSEEK_CHAT = "deepseek/deepseek-chat", MODEL_SAO10K_L3_3_EURYALE_70B = "sao10k/l3.3-euryale-70b", MODEL_OPENAI_O1 = "openai/o1", @@ -225,45 +267,40 @@ export declare enum E_OPENROUTER_MODEL { MODEL_AMAZON_NOVA_LITE_V1 = "amazon/nova-lite-v1", MODEL_AMAZON_NOVA_MICRO_V1 = "amazon/nova-micro-v1", MODEL_AMAZON_NOVA_PRO_V1 = "amazon/nova-pro-v1", - MODEL_QWEN_QWQ_32B_PREVIEW = "qwen/qwq-32b-preview", MODEL_OPENAI_GPT_4O_2024_11_20 = "openai/gpt-4o-2024-11-20", MODEL_MISTRALAI_MISTRAL_LARGE_2411 = "mistralai/mistral-large-2411", MODEL_MISTRALAI_MISTRAL_LARGE_2407 = "mistralai/mistral-large-2407", MODEL_MISTRALAI_PIXTRAL_LARGE_2411 = "mistralai/pixtral-large-2411", - MODEL_QWEN_QWEN_2_5_CODER_32B_INSTRUCT_FREE = "qwen/qwen-2.5-coder-32b-instruct:free", MODEL_QWEN_QWEN_2_5_CODER_32B_INSTRUCT = "qwen/qwen-2.5-coder-32b-instruct", MODEL_RAIFLE_SORCERERLM_8X22B = "raifle/sorcererlm-8x22b", MODEL_THEDRUMMER_UNSLOPNEMO_12B = "thedrummer/unslopnemo-12b", - MODEL_ANTHROPIC_CLAUDE_3_5_HAIKU = "anthropic/claude-3.5-haiku", MODEL_ANTHROPIC_CLAUDE_3_5_HAIKU_20241022 = "anthropic/claude-3.5-haiku-20241022", + MODEL_ANTHROPIC_CLAUDE_3_5_HAIKU = "anthropic/claude-3.5-haiku", MODEL_ANTHRACITE_ORG_MAGNUM_V4_72B = "anthracite-org/magnum-v4-72b", MODEL_ANTHROPIC_CLAUDE_3_5_SONNET = "anthropic/claude-3.5-sonnet", MODEL_MISTRALAI_MINISTRAL_8B = "mistralai/ministral-8b", MODEL_MISTRALAI_MINISTRAL_3B = "mistralai/ministral-3b", MODEL_QWEN_QWEN_2_5_7B_INSTRUCT = "qwen/qwen-2.5-7b-instruct", MODEL_NVIDIA_LLAMA_3_1_NEMOTRON_70B_INSTRUCT = "nvidia/llama-3.1-nemotron-70b-instruct", - MODEL_INFLECTION_INFLECTION_3_PRODUCTIVITY = "inflection/inflection-3-productivity", MODEL_INFLECTION_INFLECTION_3_PI = "inflection/inflection-3-pi", - MODEL_GOOGLE_GEMINI_FLASH_1_5_8B = "google/gemini-flash-1.5-8b", + MODEL_INFLECTION_INFLECTION_3_PRODUCTIVITY = "inflection/inflection-3-productivity", MODEL_THEDRUMMER_ROCINANTE_12B = "thedrummer/rocinante-12b", - MODEL_ANTHRACITE_ORG_MAGNUM_V2_72B = "anthracite-org/magnum-v2-72b", MODEL_META_LLAMA_LLAMA_3_2_3B_INSTRUCT_FREE = "meta-llama/llama-3.2-3b-instruct:free", MODEL_META_LLAMA_LLAMA_3_2_3B_INSTRUCT = "meta-llama/llama-3.2-3b-instruct", MODEL_META_LLAMA_LLAMA_3_2_1B_INSTRUCT = "meta-llama/llama-3.2-1b-instruct", MODEL_META_LLAMA_LLAMA_3_2_90B_VISION_INSTRUCT = "meta-llama/llama-3.2-90b-vision-instruct", MODEL_META_LLAMA_LLAMA_3_2_11B_VISION_INSTRUCT = "meta-llama/llama-3.2-11b-vision-instruct", - MODEL_QWEN_QWEN_2_5_72B_INSTRUCT_FREE = "qwen/qwen-2.5-72b-instruct:free", MODEL_QWEN_QWEN_2_5_72B_INSTRUCT = "qwen/qwen-2.5-72b-instruct", MODEL_NEVERSLEEP_LLAMA_3_1_LUMIMAID_8B = "neversleep/llama-3.1-lumimaid-8b", - MODEL_OPENAI_O1_MINI = "openai/o1-mini", - MODEL_OPENAI_O1_MINI_2024_09_12 = "openai/o1-mini-2024-09-12", MODEL_MISTRALAI_PIXTRAL_12B = "mistralai/pixtral-12b", - MODEL_COHERE_COMMAND_R_PLUS_08_2024 = "cohere/command-r-plus-08-2024", MODEL_COHERE_COMMAND_R_08_2024 = "cohere/command-r-08-2024", - MODEL_QWEN_QWEN_2_5_VL_7B_INSTRUCT = "qwen/qwen-2.5-vl-7b-instruct", + MODEL_COHERE_COMMAND_R_PLUS_08_2024 = "cohere/command-r-plus-08-2024", MODEL_SAO10K_L3_1_EURYALE_70B = "sao10k/l3.1-euryale-70b", + MODEL_QWEN_QWEN_2_5_VL_7B_INSTRUCT_FREE = "qwen/qwen-2.5-vl-7b-instruct:free", + MODEL_QWEN_QWEN_2_5_VL_7B_INSTRUCT = "qwen/qwen-2.5-vl-7b-instruct", MODEL_MICROSOFT_PHI_3_5_MINI_128K_INSTRUCT = "microsoft/phi-3.5-mini-128k-instruct", MODEL_NOUSRESEARCH_HERMES_3_LLAMA_3_1_70B = "nousresearch/hermes-3-llama-3.1-70b", + MODEL_NOUSRESEARCH_HERMES_3_LLAMA_3_1_405B_FREE = "nousresearch/hermes-3-llama-3.1-405b:free", MODEL_NOUSRESEARCH_HERMES_3_LLAMA_3_1_405B = "nousresearch/hermes-3-llama-3.1-405b", MODEL_OPENAI_CHATGPT_4O_LATEST = "openai/chatgpt-4o-latest", MODEL_SAO10K_L3_LUNARIS_8B = "sao10k/l3-lunaris-8b", @@ -273,14 +310,11 @@ export declare enum E_OPENROUTER_MODEL { MODEL_META_LLAMA_LLAMA_3_1_405B_INSTRUCT_FREE = "meta-llama/llama-3.1-405b-instruct:free", MODEL_META_LLAMA_LLAMA_3_1_405B_INSTRUCT = "meta-llama/llama-3.1-405b-instruct", MODEL_META_LLAMA_LLAMA_3_1_70B_INSTRUCT = "meta-llama/llama-3.1-70b-instruct", - MODEL_MISTRALAI_MISTRAL_NEMO_FREE = "mistralai/mistral-nemo:free", MODEL_MISTRALAI_MISTRAL_NEMO = "mistralai/mistral-nemo", - MODEL_OPENAI_GPT_4O_MINI = "openai/gpt-4o-mini", MODEL_OPENAI_GPT_4O_MINI_2024_07_18 = "openai/gpt-4o-mini-2024-07-18", + MODEL_OPENAI_GPT_4O_MINI = "openai/gpt-4o-mini", MODEL_GOOGLE_GEMMA_2_27B_IT = "google/gemma-2-27b-it", - MODEL_GOOGLE_GEMMA_2_9B_IT_FREE = "google/gemma-2-9b-it:free", MODEL_GOOGLE_GEMMA_2_9B_IT = "google/gemma-2-9b-it", - MODEL_ANTHROPIC_CLAUDE_3_5_SONNET_20240620 = "anthropic/claude-3.5-sonnet-20240620", MODEL_SAO10K_L3_EURYALE_70B = "sao10k/l3-euryale-70b", MODEL_NOUSRESEARCH_HERMES_2_PRO_LLAMA_3_8B = "nousresearch/hermes-2-pro-llama-3-8b", MODEL_MISTRALAI_MISTRAL_7B_INSTRUCT_FREE = "mistralai/mistral-7b-instruct:free", @@ -288,30 +322,22 @@ export declare enum E_OPENROUTER_MODEL { MODEL_MISTRALAI_MISTRAL_7B_INSTRUCT_V0_3 = "mistralai/mistral-7b-instruct-v0.3", MODEL_MICROSOFT_PHI_3_MINI_128K_INSTRUCT = "microsoft/phi-3-mini-128k-instruct", MODEL_MICROSOFT_PHI_3_MEDIUM_128K_INSTRUCT = "microsoft/phi-3-medium-128k-instruct", - MODEL_NEVERSLEEP_LLAMA_3_LUMIMAID_70B = "neversleep/llama-3-lumimaid-70b", - MODEL_GOOGLE_GEMINI_FLASH_1_5 = "google/gemini-flash-1.5", - MODEL_OPENAI_GPT_4O = "openai/gpt-4o", - MODEL_OPENAI_GPT_4O_EXTENDED = "openai/gpt-4o:extended", MODEL_META_LLAMA_LLAMA_GUARD_2_8B = "meta-llama/llama-guard-2-8b", MODEL_OPENAI_GPT_4O_2024_05_13 = "openai/gpt-4o-2024-05-13", - MODEL_META_LLAMA_LLAMA_3_8B_INSTRUCT = "meta-llama/llama-3-8b-instruct", + MODEL_OPENAI_GPT_4O = "openai/gpt-4o", + MODEL_OPENAI_GPT_4O_EXTENDED = "openai/gpt-4o:extended", MODEL_META_LLAMA_LLAMA_3_70B_INSTRUCT = "meta-llama/llama-3-70b-instruct", + MODEL_META_LLAMA_LLAMA_3_8B_INSTRUCT = "meta-llama/llama-3-8b-instruct", MODEL_MISTRALAI_MIXTRAL_8X22B_INSTRUCT = "mistralai/mixtral-8x22b-instruct", MODEL_MICROSOFT_WIZARDLM_2_8X22B = "microsoft/wizardlm-2-8x22b", - MODEL_GOOGLE_GEMINI_PRO_1_5 = "google/gemini-pro-1.5", MODEL_OPENAI_GPT_4_TURBO = "openai/gpt-4-turbo", - MODEL_COHERE_COMMAND_R_PLUS = "cohere/command-r-plus", - MODEL_COHERE_COMMAND_R_PLUS_04_2024 = "cohere/command-r-plus-04-2024", - MODEL_COHERE_COMMAND = "cohere/command", - MODEL_COHERE_COMMAND_R = "cohere/command-r", MODEL_ANTHROPIC_CLAUDE_3_HAIKU = "anthropic/claude-3-haiku", MODEL_ANTHROPIC_CLAUDE_3_OPUS = "anthropic/claude-3-opus", - MODEL_COHERE_COMMAND_R_03_2024 = "cohere/command-r-03-2024", MODEL_MISTRALAI_MISTRAL_LARGE = "mistralai/mistral-large", MODEL_OPENAI_GPT_3_5_TURBO_0613 = "openai/gpt-3.5-turbo-0613", MODEL_OPENAI_GPT_4_TURBO_PREVIEW = "openai/gpt-4-turbo-preview", - MODEL_MISTRALAI_MISTRAL_SMALL = "mistralai/mistral-small", MODEL_MISTRALAI_MISTRAL_TINY = "mistralai/mistral-tiny", + MODEL_MISTRALAI_MISTRAL_7B_INSTRUCT_V0_2 = "mistralai/mistral-7b-instruct-v0.2", MODEL_MISTRALAI_MIXTRAL_8X7B_INSTRUCT = "mistralai/mixtral-8x7b-instruct", MODEL_NEVERSLEEP_NOROMAID_20B = "neversleep/noromaid-20b", MODEL_ALPINDALE_GOLIATH_120B = "alpindale/goliath-120b", @@ -323,7 +349,7 @@ export declare enum E_OPENROUTER_MODEL { MODEL_MANCER_WEAVER = "mancer/weaver", MODEL_UNDI95_REMM_SLERP_L2_13B = "undi95/remm-slerp-l2-13b", MODEL_GRYPHE_MYTHOMAX_L2_13B = "gryphe/mythomax-l2-13b", - MODEL_OPENAI_GPT_3_5_TURBO = "openai/gpt-3.5-turbo", + MODEL_OPENAI_GPT_4_0314 = "openai/gpt-4-0314", MODEL_OPENAI_GPT_4 = "openai/gpt-4", - MODEL_OPENAI_GPT_4_0314 = "openai/gpt-4-0314" + MODEL_OPENAI_GPT_3_5_TURBO = "openai/gpt-3.5-turbo" } diff --git a/packages/kbot/dist-in/models/cache/openrouter-models.js b/packages/kbot/dist-in/models/cache/openrouter-models.js index f764f002..2cbf8cdf 100644 --- a/packages/kbot/dist-in/models/cache/openrouter-models.js +++ b/packages/kbot/dist-in/models/cache/openrouter-models.js @@ -1,10 +1,96 @@ export var E_OPENROUTER_MODEL; (function (E_OPENROUTER_MODEL) { - E_OPENROUTER_MODEL["MODEL_X_AI_GROK_4_FAST_FREE"] = "x-ai/grok-4-fast:free"; + E_OPENROUTER_MODEL["MODEL_BYTEDANCE_SEED_SEED_1_6_FLASH"] = "bytedance-seed/seed-1.6-flash"; + E_OPENROUTER_MODEL["MODEL_BYTEDANCE_SEED_SEED_1_6"] = "bytedance-seed/seed-1.6"; + E_OPENROUTER_MODEL["MODEL_MINIMAX_MINIMAX_M2_1"] = "minimax/minimax-m2.1"; + E_OPENROUTER_MODEL["MODEL_Z_AI_GLM_4_7"] = "z-ai/glm-4.7"; + E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_3_FLASH_PREVIEW"] = "google/gemini-3-flash-preview"; + E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_SMALL_CREATIVE"] = "mistralai/mistral-small-creative"; + E_OPENROUTER_MODEL["MODEL_ALLENAI_OLMO_3_1_32B_THINK_FREE"] = "allenai/olmo-3.1-32b-think:free"; + E_OPENROUTER_MODEL["MODEL_XIAOMI_MIMO_V2_FLASH_FREE"] = "xiaomi/mimo-v2-flash:free"; + E_OPENROUTER_MODEL["MODEL_NVIDIA_NEMOTRON_3_NANO_30B_A3B_FREE"] = "nvidia/nemotron-3-nano-30b-a3b:free"; + E_OPENROUTER_MODEL["MODEL_NVIDIA_NEMOTRON_3_NANO_30B_A3B"] = "nvidia/nemotron-3-nano-30b-a3b"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_5_2_CHAT"] = "openai/gpt-5.2-chat"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_5_2_PRO"] = "openai/gpt-5.2-pro"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_5_2"] = "openai/gpt-5.2"; + E_OPENROUTER_MODEL["MODEL_MISTRALAI_DEVSTRAL_2512_FREE"] = "mistralai/devstral-2512:free"; + E_OPENROUTER_MODEL["MODEL_MISTRALAI_DEVSTRAL_2512"] = "mistralai/devstral-2512"; + E_OPENROUTER_MODEL["MODEL_RELACE_RELACE_SEARCH"] = "relace/relace-search"; + E_OPENROUTER_MODEL["MODEL_Z_AI_GLM_4_6V"] = "z-ai/glm-4.6v"; + E_OPENROUTER_MODEL["MODEL_NEX_AGI_DEEPSEEK_V3_1_NEX_N1_FREE"] = "nex-agi/deepseek-v3.1-nex-n1:free"; + E_OPENROUTER_MODEL["MODEL_ESSENTIALAI_RNJ_1_INSTRUCT"] = "essentialai/rnj-1-instruct"; + E_OPENROUTER_MODEL["MODEL_OPENROUTER_BODYBUILDER"] = "openrouter/bodybuilder"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_5_1_CODEX_MAX"] = "openai/gpt-5.1-codex-max"; + E_OPENROUTER_MODEL["MODEL_AMAZON_NOVA_2_LITE_V1"] = "amazon/nova-2-lite-v1"; + E_OPENROUTER_MODEL["MODEL_MISTRALAI_MINISTRAL_14B_2512"] = "mistralai/ministral-14b-2512"; + E_OPENROUTER_MODEL["MODEL_MISTRALAI_MINISTRAL_8B_2512"] = "mistralai/ministral-8b-2512"; + E_OPENROUTER_MODEL["MODEL_MISTRALAI_MINISTRAL_3B_2512"] = "mistralai/ministral-3b-2512"; + E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_LARGE_2512"] = "mistralai/mistral-large-2512"; + E_OPENROUTER_MODEL["MODEL_ARCEE_AI_TRINITY_MINI_FREE"] = "arcee-ai/trinity-mini:free"; + E_OPENROUTER_MODEL["MODEL_ARCEE_AI_TRINITY_MINI"] = "arcee-ai/trinity-mini"; + E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_V3_2_SPECIALE"] = "deepseek/deepseek-v3.2-speciale"; + E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_V3_2"] = "deepseek/deepseek-v3.2"; + E_OPENROUTER_MODEL["MODEL_PRIME_INTELLECT_INTELLECT_3"] = "prime-intellect/intellect-3"; + E_OPENROUTER_MODEL["MODEL_TNGTECH_TNG_R1T_CHIMERA_FREE"] = "tngtech/tng-r1t-chimera:free"; + E_OPENROUTER_MODEL["MODEL_TNGTECH_TNG_R1T_CHIMERA"] = "tngtech/tng-r1t-chimera"; + E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_OPUS_4_5"] = "anthropic/claude-opus-4.5"; + E_OPENROUTER_MODEL["MODEL_ALLENAI_OLMO_3_32B_THINK_FREE"] = "allenai/olmo-3-32b-think:free"; + E_OPENROUTER_MODEL["MODEL_ALLENAI_OLMO_3_7B_INSTRUCT"] = "allenai/olmo-3-7b-instruct"; + E_OPENROUTER_MODEL["MODEL_ALLENAI_OLMO_3_7B_THINK"] = "allenai/olmo-3-7b-think"; + E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_3_PRO_IMAGE_PREVIEW"] = "google/gemini-3-pro-image-preview"; + E_OPENROUTER_MODEL["MODEL_X_AI_GROK_4_1_FAST"] = "x-ai/grok-4.1-fast"; + E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_3_PRO_PREVIEW"] = "google/gemini-3-pro-preview"; + E_OPENROUTER_MODEL["MODEL_DEEPCOGITO_COGITO_V2_1_671B"] = "deepcogito/cogito-v2.1-671b"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_5_1"] = "openai/gpt-5.1"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_5_1_CHAT"] = "openai/gpt-5.1-chat"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_5_1_CODEX"] = "openai/gpt-5.1-codex"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_5_1_CODEX_MINI"] = "openai/gpt-5.1-codex-mini"; + E_OPENROUTER_MODEL["MODEL_KWAIPILOT_KAT_CODER_PRO_FREE"] = "kwaipilot/kat-coder-pro:free"; + E_OPENROUTER_MODEL["MODEL_MOONSHOTAI_KIMI_K2_THINKING"] = "moonshotai/kimi-k2-thinking"; + E_OPENROUTER_MODEL["MODEL_AMAZON_NOVA_PREMIER_V1"] = "amazon/nova-premier-v1"; + E_OPENROUTER_MODEL["MODEL_PERPLEXITY_SONAR_PRO_SEARCH"] = "perplexity/sonar-pro-search"; + E_OPENROUTER_MODEL["MODEL_MISTRALAI_VOXTRAL_SMALL_24B_2507"] = "mistralai/voxtral-small-24b-2507"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_OSS_SAFEGUARD_20B"] = "openai/gpt-oss-safeguard-20b"; + E_OPENROUTER_MODEL["MODEL_NVIDIA_NEMOTRON_NANO_12B_V2_VL_FREE"] = "nvidia/nemotron-nano-12b-v2-vl:free"; + E_OPENROUTER_MODEL["MODEL_NVIDIA_NEMOTRON_NANO_12B_V2_VL"] = "nvidia/nemotron-nano-12b-v2-vl"; + E_OPENROUTER_MODEL["MODEL_MINIMAX_MINIMAX_M2"] = "minimax/minimax-m2"; + E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_VL_32B_INSTRUCT"] = "qwen/qwen3-vl-32b-instruct"; + E_OPENROUTER_MODEL["MODEL_LIQUID_LFM2_8B_A1B"] = "liquid/lfm2-8b-a1b"; + E_OPENROUTER_MODEL["MODEL_LIQUID_LFM_2_2_6B"] = "liquid/lfm-2.2-6b"; + E_OPENROUTER_MODEL["MODEL_IBM_GRANITE_GRANITE_4_0_H_MICRO"] = "ibm-granite/granite-4.0-h-micro"; + E_OPENROUTER_MODEL["MODEL_DEEPCOGITO_COGITO_V2_PREVIEW_LLAMA_405B"] = "deepcogito/cogito-v2-preview-llama-405b"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_5_IMAGE_MINI"] = "openai/gpt-5-image-mini"; + E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_HAIKU_4_5"] = "anthropic/claude-haiku-4.5"; + E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_VL_8B_THINKING"] = "qwen/qwen3-vl-8b-thinking"; + E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_VL_8B_INSTRUCT"] = "qwen/qwen3-vl-8b-instruct"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_5_IMAGE"] = "openai/gpt-5-image"; + E_OPENROUTER_MODEL["MODEL_OPENAI_O3_DEEP_RESEARCH"] = "openai/o3-deep-research"; + E_OPENROUTER_MODEL["MODEL_OPENAI_O4_MINI_DEEP_RESEARCH"] = "openai/o4-mini-deep-research"; + E_OPENROUTER_MODEL["MODEL_NVIDIA_LLAMA_3_3_NEMOTRON_SUPER_49B_V1_5"] = "nvidia/llama-3.3-nemotron-super-49b-v1.5"; + E_OPENROUTER_MODEL["MODEL_BAIDU_ERNIE_4_5_21B_A3B_THINKING"] = "baidu/ernie-4.5-21b-a3b-thinking"; + E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_2_5_FLASH_IMAGE"] = "google/gemini-2.5-flash-image"; + E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_VL_30B_A3B_THINKING"] = "qwen/qwen3-vl-30b-a3b-thinking"; + E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_VL_30B_A3B_INSTRUCT"] = "qwen/qwen3-vl-30b-a3b-instruct"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_5_PRO"] = "openai/gpt-5-pro"; + E_OPENROUTER_MODEL["MODEL_Z_AI_GLM_4_6"] = "z-ai/glm-4.6"; + E_OPENROUTER_MODEL["MODEL_Z_AI_GLM_4_6_EXACTO"] = "z-ai/glm-4.6:exacto"; + E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_SONNET_4_5"] = "anthropic/claude-sonnet-4.5"; + E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_V3_2_EXP"] = "deepseek/deepseek-v3.2-exp"; + E_OPENROUTER_MODEL["MODEL_THEDRUMMER_CYDONIA_24B_V4_1"] = "thedrummer/cydonia-24b-v4.1"; + E_OPENROUTER_MODEL["MODEL_RELACE_RELACE_APPLY_3"] = "relace/relace-apply-3"; + E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_2_5_FLASH_PREVIEW_09_2025"] = "google/gemini-2.5-flash-preview-09-2025"; + E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_2_5_FLASH_LITE_PREVIEW_09_2025"] = "google/gemini-2.5-flash-lite-preview-09-2025"; + E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_VL_235B_A22B_THINKING"] = "qwen/qwen3-vl-235b-a22b-thinking"; + E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_VL_235B_A22B_INSTRUCT"] = "qwen/qwen3-vl-235b-a22b-instruct"; + E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_MAX"] = "qwen/qwen3-max"; + E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_CODER_PLUS"] = "qwen/qwen3-coder-plus"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_5_CODEX"] = "openai/gpt-5-codex"; + E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_V3_1_TERMINUS_EXACTO"] = "deepseek/deepseek-v3.1-terminus:exacto"; + E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_V3_1_TERMINUS"] = "deepseek/deepseek-v3.1-terminus"; + E_OPENROUTER_MODEL["MODEL_X_AI_GROK_4_FAST"] = "x-ai/grok-4-fast"; + E_OPENROUTER_MODEL["MODEL_ALIBABA_TONGYI_DEEPRESEARCH_30B_A3B_FREE"] = "alibaba/tongyi-deepresearch-30b-a3b:free"; E_OPENROUTER_MODEL["MODEL_ALIBABA_TONGYI_DEEPRESEARCH_30B_A3B"] = "alibaba/tongyi-deepresearch-30b-a3b"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_CODER_FLASH"] = "qwen/qwen3-coder-flash"; - E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_CODER_PLUS"] = "qwen/qwen3-coder-plus"; - E_OPENROUTER_MODEL["MODEL_ARCEE_AI_AFM_4_5B"] = "arcee-ai/afm-4.5b"; E_OPENROUTER_MODEL["MODEL_OPENGVLAB_INTERNVL3_78B"] = "opengvlab/internvl3-78b"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_NEXT_80B_A3B_THINKING"] = "qwen/qwen3-next-80b-a3b-thinking"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_NEXT_80B_A3B_INSTRUCT"] = "qwen/qwen3-next-80b-a3b-instruct"; @@ -13,20 +99,17 @@ export var E_OPENROUTER_MODEL; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN_PLUS_2025_07_28_THINKING"] = "qwen/qwen-plus-2025-07-28:thinking"; E_OPENROUTER_MODEL["MODEL_NVIDIA_NEMOTRON_NANO_9B_V2_FREE"] = "nvidia/nemotron-nano-9b-v2:free"; E_OPENROUTER_MODEL["MODEL_NVIDIA_NEMOTRON_NANO_9B_V2"] = "nvidia/nemotron-nano-9b-v2"; - E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_MAX"] = "qwen/qwen3-max"; E_OPENROUTER_MODEL["MODEL_MOONSHOTAI_KIMI_K2_0905"] = "moonshotai/kimi-k2-0905"; - E_OPENROUTER_MODEL["MODEL_BYTEDANCE_SEED_OSS_36B_INSTRUCT"] = "bytedance/seed-oss-36b-instruct"; + E_OPENROUTER_MODEL["MODEL_MOONSHOTAI_KIMI_K2_0905_EXACTO"] = "moonshotai/kimi-k2-0905:exacto"; + E_OPENROUTER_MODEL["MODEL_DEEPCOGITO_COGITO_V2_PREVIEW_LLAMA_70B"] = "deepcogito/cogito-v2-preview-llama-70b"; E_OPENROUTER_MODEL["MODEL_DEEPCOGITO_COGITO_V2_PREVIEW_LLAMA_109B_MOE"] = "deepcogito/cogito-v2-preview-llama-109b-moe"; - E_OPENROUTER_MODEL["MODEL_DEEPCOGITO_COGITO_V2_PREVIEW_DEEPSEEK_671B"] = "deepcogito/cogito-v2-preview-deepseek-671b"; E_OPENROUTER_MODEL["MODEL_STEPFUN_AI_STEP3"] = "stepfun-ai/step3"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_30B_A3B_THINKING_2507"] = "qwen/qwen3-30b-a3b-thinking-2507"; E_OPENROUTER_MODEL["MODEL_X_AI_GROK_CODE_FAST_1"] = "x-ai/grok-code-fast-1"; E_OPENROUTER_MODEL["MODEL_NOUSRESEARCH_HERMES_4_70B"] = "nousresearch/hermes-4-70b"; E_OPENROUTER_MODEL["MODEL_NOUSRESEARCH_HERMES_4_405B"] = "nousresearch/hermes-4-405b"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_2_5_FLASH_IMAGE_PREVIEW"] = "google/gemini-2.5-flash-image-preview"; - E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_CHAT_V3_1_FREE"] = "deepseek/deepseek-chat-v3.1:free"; E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_CHAT_V3_1"] = "deepseek/deepseek-chat-v3.1"; - E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_V3_1_BASE"] = "deepseek/deepseek-v3.1-base"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4O_AUDIO_PREVIEW"] = "openai/gpt-4o-audio-preview"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_MEDIUM_3_1"] = "mistralai/mistral-medium-3.1"; E_OPENROUTER_MODEL["MODEL_BAIDU_ERNIE_4_5_21B_A3B"] = "baidu/ernie-4.5-21b-a3b"; @@ -40,6 +123,7 @@ export var E_OPENROUTER_MODEL; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_5_NANO"] = "openai/gpt-5-nano"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_OSS_120B_FREE"] = "openai/gpt-oss-120b:free"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_OSS_120B"] = "openai/gpt-oss-120b"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_OSS_120B_EXACTO"] = "openai/gpt-oss-120b:exacto"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_OSS_20B_FREE"] = "openai/gpt-oss-20b:free"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_OSS_20B"] = "openai/gpt-oss-20b"; E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_OPUS_4_1"] = "anthropic/claude-opus-4.1"; @@ -53,6 +137,7 @@ export var E_OPENROUTER_MODEL; E_OPENROUTER_MODEL["MODEL_Z_AI_GLM_4_32B"] = "z-ai/glm-4-32b"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_CODER_FREE"] = "qwen/qwen3-coder:free"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_CODER"] = "qwen/qwen3-coder"; + E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_CODER_EXACTO"] = "qwen/qwen3-coder:exacto"; E_OPENROUTER_MODEL["MODEL_BYTEDANCE_UI_TARS_1_5_7B"] = "bytedance/ui-tars-1.5-7b"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_2_5_FLASH_LITE"] = "google/gemini-2.5-flash-lite"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_235B_A22B_2507"] = "qwen/qwen3-235b-a22b-2507"; @@ -65,42 +150,32 @@ export var E_OPENROUTER_MODEL; E_OPENROUTER_MODEL["MODEL_COGNITIVECOMPUTATIONS_DOLPHIN_MISTRAL_24B_VENICE_EDITION_FREE"] = "cognitivecomputations/dolphin-mistral-24b-venice-edition:free"; E_OPENROUTER_MODEL["MODEL_X_AI_GROK_4"] = "x-ai/grok-4"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMMA_3N_E2B_IT_FREE"] = "google/gemma-3n-e2b-it:free"; - E_OPENROUTER_MODEL["MODEL_TENCENT_HUNYUAN_A13B_INSTRUCT_FREE"] = "tencent/hunyuan-a13b-instruct:free"; E_OPENROUTER_MODEL["MODEL_TENCENT_HUNYUAN_A13B_INSTRUCT"] = "tencent/hunyuan-a13b-instruct"; E_OPENROUTER_MODEL["MODEL_TNGTECH_DEEPSEEK_R1T2_CHIMERA_FREE"] = "tngtech/deepseek-r1t2-chimera:free"; + E_OPENROUTER_MODEL["MODEL_TNGTECH_DEEPSEEK_R1T2_CHIMERA"] = "tngtech/deepseek-r1t2-chimera"; E_OPENROUTER_MODEL["MODEL_MORPH_MORPH_V3_LARGE"] = "morph/morph-v3-large"; E_OPENROUTER_MODEL["MODEL_MORPH_MORPH_V3_FAST"] = "morph/morph-v3-fast"; E_OPENROUTER_MODEL["MODEL_BAIDU_ERNIE_4_5_VL_424B_A47B"] = "baidu/ernie-4.5-vl-424b-a47b"; E_OPENROUTER_MODEL["MODEL_BAIDU_ERNIE_4_5_300B_A47B"] = "baidu/ernie-4.5-300b-a47b"; - E_OPENROUTER_MODEL["MODEL_THEDRUMMER_ANUBIS_70B_V1_1"] = "thedrummer/anubis-70b-v1.1"; E_OPENROUTER_MODEL["MODEL_INCEPTION_MERCURY"] = "inception/mercury"; - E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_SMALL_3_2_24B_INSTRUCT_FREE"] = "mistralai/mistral-small-3.2-24b-instruct:free"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_SMALL_3_2_24B_INSTRUCT"] = "mistralai/mistral-small-3.2-24b-instruct"; E_OPENROUTER_MODEL["MODEL_MINIMAX_MINIMAX_M1"] = "minimax/minimax-m1"; - E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_2_5_FLASH_LITE_PREVIEW_06_17"] = "google/gemini-2.5-flash-lite-preview-06-17"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_2_5_FLASH"] = "google/gemini-2.5-flash"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_2_5_PRO"] = "google/gemini-2.5-pro"; - E_OPENROUTER_MODEL["MODEL_MOONSHOTAI_KIMI_DEV_72B_FREE"] = "moonshotai/kimi-dev-72b:free"; E_OPENROUTER_MODEL["MODEL_MOONSHOTAI_KIMI_DEV_72B"] = "moonshotai/kimi-dev-72b"; E_OPENROUTER_MODEL["MODEL_OPENAI_O3_PRO"] = "openai/o3-pro"; E_OPENROUTER_MODEL["MODEL_X_AI_GROK_3_MINI"] = "x-ai/grok-3-mini"; E_OPENROUTER_MODEL["MODEL_X_AI_GROK_3"] = "x-ai/grok-3"; - E_OPENROUTER_MODEL["MODEL_MISTRALAI_MAGISTRAL_SMALL_2506"] = "mistralai/magistral-small-2506"; - E_OPENROUTER_MODEL["MODEL_MISTRALAI_MAGISTRAL_MEDIUM_2506"] = "mistralai/magistral-medium-2506"; - E_OPENROUTER_MODEL["MODEL_MISTRALAI_MAGISTRAL_MEDIUM_2506_THINKING"] = "mistralai/magistral-medium-2506:thinking"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_2_5_PRO_PREVIEW"] = "google/gemini-2.5-pro-preview"; - E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_R1_0528_QWEN3_8B_FREE"] = "deepseek/deepseek-r1-0528-qwen3-8b:free"; E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_R1_0528_QWEN3_8B"] = "deepseek/deepseek-r1-0528-qwen3-8b"; E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_R1_0528_FREE"] = "deepseek/deepseek-r1-0528:free"; E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_R1_0528"] = "deepseek/deepseek-r1-0528"; E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_OPUS_4"] = "anthropic/claude-opus-4"; E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_SONNET_4"] = "anthropic/claude-sonnet-4"; - E_OPENROUTER_MODEL["MODEL_MISTRALAI_DEVSTRAL_SMALL_2505_FREE"] = "mistralai/devstral-small-2505:free"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_DEVSTRAL_SMALL_2505"] = "mistralai/devstral-small-2505"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMMA_3N_E4B_IT_FREE"] = "google/gemma-3n-e4b-it:free"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMMA_3N_E4B_IT"] = "google/gemma-3n-e4b-it"; E_OPENROUTER_MODEL["MODEL_OPENAI_CODEX_MINI"] = "openai/codex-mini"; - E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_3_8B_INSTRUCT_FREE"] = "meta-llama/llama-3.3-8b-instruct:free"; E_OPENROUTER_MODEL["MODEL_NOUSRESEARCH_DEEPHERMES_3_MISTRAL_24B_PREVIEW"] = "nousresearch/deephermes-3-mistral-24b-preview"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_MEDIUM_3"] = "mistralai/mistral-medium-3"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_2_5_PRO_PREVIEW_05_06"] = "google/gemini-2.5-pro-preview-05-06"; @@ -113,47 +188,29 @@ export var E_OPENROUTER_MODEL; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_4B_FREE"] = "qwen/qwen3-4b:free"; E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_PROVER_V2"] = "deepseek/deepseek-prover-v2"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_GUARD_4_12B"] = "meta-llama/llama-guard-4-12b"; - E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_30B_A3B_FREE"] = "qwen/qwen3-30b-a3b:free"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_30B_A3B"] = "qwen/qwen3-30b-a3b"; - E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_8B_FREE"] = "qwen/qwen3-8b:free"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_8B"] = "qwen/qwen3-8b"; - E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_14B_FREE"] = "qwen/qwen3-14b:free"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_14B"] = "qwen/qwen3-14b"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_32B"] = "qwen/qwen3-32b"; - E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_235B_A22B_FREE"] = "qwen/qwen3-235b-a22b:free"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_235B_A22B"] = "qwen/qwen3-235b-a22b"; E_OPENROUTER_MODEL["MODEL_TNGTECH_DEEPSEEK_R1T_CHIMERA_FREE"] = "tngtech/deepseek-r1t-chimera:free"; E_OPENROUTER_MODEL["MODEL_TNGTECH_DEEPSEEK_R1T_CHIMERA"] = "tngtech/deepseek-r1t-chimera"; - E_OPENROUTER_MODEL["MODEL_MICROSOFT_MAI_DS_R1_FREE"] = "microsoft/mai-ds-r1:free"; - E_OPENROUTER_MODEL["MODEL_MICROSOFT_MAI_DS_R1"] = "microsoft/mai-ds-r1"; - E_OPENROUTER_MODEL["MODEL_THUDM_GLM_Z1_32B"] = "thudm/glm-z1-32b"; E_OPENROUTER_MODEL["MODEL_OPENAI_O4_MINI_HIGH"] = "openai/o4-mini-high"; E_OPENROUTER_MODEL["MODEL_OPENAI_O3"] = "openai/o3"; E_OPENROUTER_MODEL["MODEL_OPENAI_O4_MINI"] = "openai/o4-mini"; - E_OPENROUTER_MODEL["MODEL_SHISA_AI_SHISA_V2_LLAMA3_3_70B_FREE"] = "shisa-ai/shisa-v2-llama3.3-70b:free"; - E_OPENROUTER_MODEL["MODEL_SHISA_AI_SHISA_V2_LLAMA3_3_70B"] = "shisa-ai/shisa-v2-llama3.3-70b"; + E_OPENROUTER_MODEL["MODEL_QWEN_QWEN2_5_CODER_7B_INSTRUCT"] = "qwen/qwen2.5-coder-7b-instruct"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4_1"] = "openai/gpt-4.1"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4_1_MINI"] = "openai/gpt-4.1-mini"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4_1_NANO"] = "openai/gpt-4.1-nano"; E_OPENROUTER_MODEL["MODEL_ELEUTHERAI_LLEMMA_7B"] = "eleutherai/llemma_7b"; E_OPENROUTER_MODEL["MODEL_ALFREDPROS_CODELLAMA_7B_INSTRUCT_SOLIDITY"] = "alfredpros/codellama-7b-instruct-solidity"; - E_OPENROUTER_MODEL["MODEL_ARLIAI_QWQ_32B_ARLIAI_RPR_V1_FREE"] = "arliai/qwq-32b-arliai-rpr-v1:free"; E_OPENROUTER_MODEL["MODEL_ARLIAI_QWQ_32B_ARLIAI_RPR_V1"] = "arliai/qwq-32b-arliai-rpr-v1"; - E_OPENROUTER_MODEL["MODEL_AGENTICA_ORG_DEEPCODER_14B_PREVIEW_FREE"] = "agentica-org/deepcoder-14b-preview:free"; - E_OPENROUTER_MODEL["MODEL_AGENTICA_ORG_DEEPCODER_14B_PREVIEW"] = "agentica-org/deepcoder-14b-preview"; - E_OPENROUTER_MODEL["MODEL_MOONSHOTAI_KIMI_VL_A3B_THINKING_FREE"] = "moonshotai/kimi-vl-a3b-thinking:free"; - E_OPENROUTER_MODEL["MODEL_MOONSHOTAI_KIMI_VL_A3B_THINKING"] = "moonshotai/kimi-vl-a3b-thinking"; E_OPENROUTER_MODEL["MODEL_X_AI_GROK_3_MINI_BETA"] = "x-ai/grok-3-mini-beta"; E_OPENROUTER_MODEL["MODEL_X_AI_GROK_3_BETA"] = "x-ai/grok-3-beta"; E_OPENROUTER_MODEL["MODEL_NVIDIA_LLAMA_3_1_NEMOTRON_ULTRA_253B_V1"] = "nvidia/llama-3.1-nemotron-ultra-253b-v1"; - E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_4_MAVERICK_FREE"] = "meta-llama/llama-4-maverick:free"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_4_MAVERICK"] = "meta-llama/llama-4-maverick"; - E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_4_SCOUT_FREE"] = "meta-llama/llama-4-scout:free"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_4_SCOUT"] = "meta-llama/llama-4-scout"; - E_OPENROUTER_MODEL["MODEL_ALLENAI_MOLMO_7B_D"] = "allenai/molmo-7b-d"; - E_OPENROUTER_MODEL["MODEL_QWEN_QWEN2_5_VL_32B_INSTRUCT_FREE"] = "qwen/qwen2.5-vl-32b-instruct:free"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN2_5_VL_32B_INSTRUCT"] = "qwen/qwen2.5-vl-32b-instruct"; - E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_CHAT_V3_0324_FREE"] = "deepseek/deepseek-chat-v3-0324:free"; E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_CHAT_V3_0324"] = "deepseek/deepseek-chat-v3-0324"; E_OPENROUTER_MODEL["MODEL_OPENAI_O1_PRO"] = "openai/o1-pro"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_SMALL_3_1_24B_INSTRUCT_FREE"] = "mistralai/mistral-small-3.1-24b-instruct:free"; @@ -168,27 +225,18 @@ export var E_OPENROUTER_MODEL; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4O_SEARCH_PREVIEW"] = "openai/gpt-4o-search-preview"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMMA_3_27B_IT_FREE"] = "google/gemma-3-27b-it:free"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMMA_3_27B_IT"] = "google/gemma-3-27b-it"; - E_OPENROUTER_MODEL["MODEL_THEDRUMMER_ANUBIS_PRO_105B_V1"] = "thedrummer/anubis-pro-105b-v1"; E_OPENROUTER_MODEL["MODEL_THEDRUMMER_SKYFALL_36B_V2"] = "thedrummer/skyfall-36b-v2"; E_OPENROUTER_MODEL["MODEL_MICROSOFT_PHI_4_MULTIMODAL_INSTRUCT"] = "microsoft/phi-4-multimodal-instruct"; E_OPENROUTER_MODEL["MODEL_PERPLEXITY_SONAR_REASONING_PRO"] = "perplexity/sonar-reasoning-pro"; E_OPENROUTER_MODEL["MODEL_PERPLEXITY_SONAR_PRO"] = "perplexity/sonar-pro"; E_OPENROUTER_MODEL["MODEL_PERPLEXITY_SONAR_DEEP_RESEARCH"] = "perplexity/sonar-deep-research"; - E_OPENROUTER_MODEL["MODEL_QWEN_QWQ_32B_FREE"] = "qwen/qwq-32b:free"; E_OPENROUTER_MODEL["MODEL_QWEN_QWQ_32B"] = "qwen/qwq-32b"; - E_OPENROUTER_MODEL["MODEL_NOUSRESEARCH_DEEPHERMES_3_LLAMA_3_8B_PREVIEW_FREE"] = "nousresearch/deephermes-3-llama-3-8b-preview:free"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_2_0_FLASH_LITE_001"] = "google/gemini-2.0-flash-lite-001"; - E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_3_7_SONNET"] = "anthropic/claude-3.7-sonnet"; E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_3_7_SONNET_THINKING"] = "anthropic/claude-3.7-sonnet:thinking"; - E_OPENROUTER_MODEL["MODEL_PERPLEXITY_R1_1776"] = "perplexity/r1-1776"; + E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_3_7_SONNET"] = "anthropic/claude-3.7-sonnet"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_SABA"] = "mistralai/mistral-saba"; - E_OPENROUTER_MODEL["MODEL_COGNITIVECOMPUTATIONS_DOLPHIN3_0_R1_MISTRAL_24B_FREE"] = "cognitivecomputations/dolphin3.0-r1-mistral-24b:free"; - E_OPENROUTER_MODEL["MODEL_COGNITIVECOMPUTATIONS_DOLPHIN3_0_R1_MISTRAL_24B"] = "cognitivecomputations/dolphin3.0-r1-mistral-24b"; - E_OPENROUTER_MODEL["MODEL_COGNITIVECOMPUTATIONS_DOLPHIN3_0_MISTRAL_24B_FREE"] = "cognitivecomputations/dolphin3.0-mistral-24b:free"; - E_OPENROUTER_MODEL["MODEL_COGNITIVECOMPUTATIONS_DOLPHIN3_0_MISTRAL_24B"] = "cognitivecomputations/dolphin3.0-mistral-24b"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_GUARD_3_8B"] = "meta-llama/llama-guard-3-8b"; E_OPENROUTER_MODEL["MODEL_OPENAI_O3_MINI_HIGH"] = "openai/o3-mini-high"; - E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_R1_DISTILL_LLAMA_8B"] = "deepseek/deepseek-r1-distill-llama-8b"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_2_0_FLASH_001"] = "google/gemini-2.0-flash-001"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN_VL_PLUS"] = "qwen/qwen-vl-plus"; E_OPENROUTER_MODEL["MODEL_AION_LABS_AION_1_0"] = "aion-labs/aion-1.0"; @@ -196,26 +244,20 @@ export var E_OPENROUTER_MODEL; E_OPENROUTER_MODEL["MODEL_AION_LABS_AION_RP_LLAMA_3_1_8B"] = "aion-labs/aion-rp-llama-3.1-8b"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN_VL_MAX"] = "qwen/qwen-vl-max"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN_TURBO"] = "qwen/qwen-turbo"; - E_OPENROUTER_MODEL["MODEL_QWEN_QWEN2_5_VL_72B_INSTRUCT_FREE"] = "qwen/qwen2.5-vl-72b-instruct:free"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN2_5_VL_72B_INSTRUCT"] = "qwen/qwen2.5-vl-72b-instruct"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN_PLUS"] = "qwen/qwen-plus"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN_MAX"] = "qwen/qwen-max"; E_OPENROUTER_MODEL["MODEL_OPENAI_O3_MINI"] = "openai/o3-mini"; - E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_SMALL_24B_INSTRUCT_2501_FREE"] = "mistralai/mistral-small-24b-instruct-2501:free"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_SMALL_24B_INSTRUCT_2501"] = "mistralai/mistral-small-24b-instruct-2501"; E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_R1_DISTILL_QWEN_32B"] = "deepseek/deepseek-r1-distill-qwen-32b"; E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_R1_DISTILL_QWEN_14B"] = "deepseek/deepseek-r1-distill-qwen-14b"; E_OPENROUTER_MODEL["MODEL_PERPLEXITY_SONAR_REASONING"] = "perplexity/sonar-reasoning"; E_OPENROUTER_MODEL["MODEL_PERPLEXITY_SONAR"] = "perplexity/sonar"; - E_OPENROUTER_MODEL["MODEL_LIQUID_LFM_7B"] = "liquid/lfm-7b"; - E_OPENROUTER_MODEL["MODEL_LIQUID_LFM_3B"] = "liquid/lfm-3b"; - E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_R1_DISTILL_LLAMA_70B_FREE"] = "deepseek/deepseek-r1-distill-llama-70b:free"; E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_R1_DISTILL_LLAMA_70B"] = "deepseek/deepseek-r1-distill-llama-70b"; - E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_R1_FREE"] = "deepseek/deepseek-r1:free"; E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_R1"] = "deepseek/deepseek-r1"; E_OPENROUTER_MODEL["MODEL_MINIMAX_MINIMAX_01"] = "minimax/minimax-01"; - E_OPENROUTER_MODEL["MODEL_MISTRALAI_CODESTRAL_2501"] = "mistralai/codestral-2501"; E_OPENROUTER_MODEL["MODEL_MICROSOFT_PHI_4"] = "microsoft/phi-4"; + E_OPENROUTER_MODEL["MODEL_SAO10K_L3_1_70B_HANAMI_X1"] = "sao10k/l3.1-70b-hanami-x1"; E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_CHAT"] = "deepseek/deepseek-chat"; E_OPENROUTER_MODEL["MODEL_SAO10K_L3_3_EURYALE_70B"] = "sao10k/l3.3-euryale-70b"; E_OPENROUTER_MODEL["MODEL_OPENAI_O1"] = "openai/o1"; @@ -226,45 +268,40 @@ export var E_OPENROUTER_MODEL; E_OPENROUTER_MODEL["MODEL_AMAZON_NOVA_LITE_V1"] = "amazon/nova-lite-v1"; E_OPENROUTER_MODEL["MODEL_AMAZON_NOVA_MICRO_V1"] = "amazon/nova-micro-v1"; E_OPENROUTER_MODEL["MODEL_AMAZON_NOVA_PRO_V1"] = "amazon/nova-pro-v1"; - E_OPENROUTER_MODEL["MODEL_QWEN_QWQ_32B_PREVIEW"] = "qwen/qwq-32b-preview"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4O_2024_11_20"] = "openai/gpt-4o-2024-11-20"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_LARGE_2411"] = "mistralai/mistral-large-2411"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_LARGE_2407"] = "mistralai/mistral-large-2407"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_PIXTRAL_LARGE_2411"] = "mistralai/pixtral-large-2411"; - E_OPENROUTER_MODEL["MODEL_QWEN_QWEN_2_5_CODER_32B_INSTRUCT_FREE"] = "qwen/qwen-2.5-coder-32b-instruct:free"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN_2_5_CODER_32B_INSTRUCT"] = "qwen/qwen-2.5-coder-32b-instruct"; E_OPENROUTER_MODEL["MODEL_RAIFLE_SORCERERLM_8X22B"] = "raifle/sorcererlm-8x22b"; E_OPENROUTER_MODEL["MODEL_THEDRUMMER_UNSLOPNEMO_12B"] = "thedrummer/unslopnemo-12b"; - E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_3_5_HAIKU"] = "anthropic/claude-3.5-haiku"; E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_3_5_HAIKU_20241022"] = "anthropic/claude-3.5-haiku-20241022"; + E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_3_5_HAIKU"] = "anthropic/claude-3.5-haiku"; E_OPENROUTER_MODEL["MODEL_ANTHRACITE_ORG_MAGNUM_V4_72B"] = "anthracite-org/magnum-v4-72b"; E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_3_5_SONNET"] = "anthropic/claude-3.5-sonnet"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MINISTRAL_8B"] = "mistralai/ministral-8b"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MINISTRAL_3B"] = "mistralai/ministral-3b"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN_2_5_7B_INSTRUCT"] = "qwen/qwen-2.5-7b-instruct"; E_OPENROUTER_MODEL["MODEL_NVIDIA_LLAMA_3_1_NEMOTRON_70B_INSTRUCT"] = "nvidia/llama-3.1-nemotron-70b-instruct"; - E_OPENROUTER_MODEL["MODEL_INFLECTION_INFLECTION_3_PRODUCTIVITY"] = "inflection/inflection-3-productivity"; E_OPENROUTER_MODEL["MODEL_INFLECTION_INFLECTION_3_PI"] = "inflection/inflection-3-pi"; - E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_FLASH_1_5_8B"] = "google/gemini-flash-1.5-8b"; + E_OPENROUTER_MODEL["MODEL_INFLECTION_INFLECTION_3_PRODUCTIVITY"] = "inflection/inflection-3-productivity"; E_OPENROUTER_MODEL["MODEL_THEDRUMMER_ROCINANTE_12B"] = "thedrummer/rocinante-12b"; - E_OPENROUTER_MODEL["MODEL_ANTHRACITE_ORG_MAGNUM_V2_72B"] = "anthracite-org/magnum-v2-72b"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_2_3B_INSTRUCT_FREE"] = "meta-llama/llama-3.2-3b-instruct:free"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_2_3B_INSTRUCT"] = "meta-llama/llama-3.2-3b-instruct"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_2_1B_INSTRUCT"] = "meta-llama/llama-3.2-1b-instruct"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_2_90B_VISION_INSTRUCT"] = "meta-llama/llama-3.2-90b-vision-instruct"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_2_11B_VISION_INSTRUCT"] = "meta-llama/llama-3.2-11b-vision-instruct"; - E_OPENROUTER_MODEL["MODEL_QWEN_QWEN_2_5_72B_INSTRUCT_FREE"] = "qwen/qwen-2.5-72b-instruct:free"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN_2_5_72B_INSTRUCT"] = "qwen/qwen-2.5-72b-instruct"; E_OPENROUTER_MODEL["MODEL_NEVERSLEEP_LLAMA_3_1_LUMIMAID_8B"] = "neversleep/llama-3.1-lumimaid-8b"; - E_OPENROUTER_MODEL["MODEL_OPENAI_O1_MINI"] = "openai/o1-mini"; - E_OPENROUTER_MODEL["MODEL_OPENAI_O1_MINI_2024_09_12"] = "openai/o1-mini-2024-09-12"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_PIXTRAL_12B"] = "mistralai/pixtral-12b"; - E_OPENROUTER_MODEL["MODEL_COHERE_COMMAND_R_PLUS_08_2024"] = "cohere/command-r-plus-08-2024"; E_OPENROUTER_MODEL["MODEL_COHERE_COMMAND_R_08_2024"] = "cohere/command-r-08-2024"; - E_OPENROUTER_MODEL["MODEL_QWEN_QWEN_2_5_VL_7B_INSTRUCT"] = "qwen/qwen-2.5-vl-7b-instruct"; + E_OPENROUTER_MODEL["MODEL_COHERE_COMMAND_R_PLUS_08_2024"] = "cohere/command-r-plus-08-2024"; E_OPENROUTER_MODEL["MODEL_SAO10K_L3_1_EURYALE_70B"] = "sao10k/l3.1-euryale-70b"; + E_OPENROUTER_MODEL["MODEL_QWEN_QWEN_2_5_VL_7B_INSTRUCT_FREE"] = "qwen/qwen-2.5-vl-7b-instruct:free"; + E_OPENROUTER_MODEL["MODEL_QWEN_QWEN_2_5_VL_7B_INSTRUCT"] = "qwen/qwen-2.5-vl-7b-instruct"; E_OPENROUTER_MODEL["MODEL_MICROSOFT_PHI_3_5_MINI_128K_INSTRUCT"] = "microsoft/phi-3.5-mini-128k-instruct"; E_OPENROUTER_MODEL["MODEL_NOUSRESEARCH_HERMES_3_LLAMA_3_1_70B"] = "nousresearch/hermes-3-llama-3.1-70b"; + E_OPENROUTER_MODEL["MODEL_NOUSRESEARCH_HERMES_3_LLAMA_3_1_405B_FREE"] = "nousresearch/hermes-3-llama-3.1-405b:free"; E_OPENROUTER_MODEL["MODEL_NOUSRESEARCH_HERMES_3_LLAMA_3_1_405B"] = "nousresearch/hermes-3-llama-3.1-405b"; E_OPENROUTER_MODEL["MODEL_OPENAI_CHATGPT_4O_LATEST"] = "openai/chatgpt-4o-latest"; E_OPENROUTER_MODEL["MODEL_SAO10K_L3_LUNARIS_8B"] = "sao10k/l3-lunaris-8b"; @@ -274,14 +311,11 @@ export var E_OPENROUTER_MODEL; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_1_405B_INSTRUCT_FREE"] = "meta-llama/llama-3.1-405b-instruct:free"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_1_405B_INSTRUCT"] = "meta-llama/llama-3.1-405b-instruct"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_1_70B_INSTRUCT"] = "meta-llama/llama-3.1-70b-instruct"; - E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_NEMO_FREE"] = "mistralai/mistral-nemo:free"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_NEMO"] = "mistralai/mistral-nemo"; - E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4O_MINI"] = "openai/gpt-4o-mini"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4O_MINI_2024_07_18"] = "openai/gpt-4o-mini-2024-07-18"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4O_MINI"] = "openai/gpt-4o-mini"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMMA_2_27B_IT"] = "google/gemma-2-27b-it"; - E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMMA_2_9B_IT_FREE"] = "google/gemma-2-9b-it:free"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMMA_2_9B_IT"] = "google/gemma-2-9b-it"; - E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_3_5_SONNET_20240620"] = "anthropic/claude-3.5-sonnet-20240620"; E_OPENROUTER_MODEL["MODEL_SAO10K_L3_EURYALE_70B"] = "sao10k/l3-euryale-70b"; E_OPENROUTER_MODEL["MODEL_NOUSRESEARCH_HERMES_2_PRO_LLAMA_3_8B"] = "nousresearch/hermes-2-pro-llama-3-8b"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_7B_INSTRUCT_FREE"] = "mistralai/mistral-7b-instruct:free"; @@ -289,30 +323,22 @@ export var E_OPENROUTER_MODEL; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_7B_INSTRUCT_V0_3"] = "mistralai/mistral-7b-instruct-v0.3"; E_OPENROUTER_MODEL["MODEL_MICROSOFT_PHI_3_MINI_128K_INSTRUCT"] = "microsoft/phi-3-mini-128k-instruct"; E_OPENROUTER_MODEL["MODEL_MICROSOFT_PHI_3_MEDIUM_128K_INSTRUCT"] = "microsoft/phi-3-medium-128k-instruct"; - E_OPENROUTER_MODEL["MODEL_NEVERSLEEP_LLAMA_3_LUMIMAID_70B"] = "neversleep/llama-3-lumimaid-70b"; - E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_FLASH_1_5"] = "google/gemini-flash-1.5"; - E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4O"] = "openai/gpt-4o"; - E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4O_EXTENDED"] = "openai/gpt-4o:extended"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_GUARD_2_8B"] = "meta-llama/llama-guard-2-8b"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4O_2024_05_13"] = "openai/gpt-4o-2024-05-13"; - E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_8B_INSTRUCT"] = "meta-llama/llama-3-8b-instruct"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4O"] = "openai/gpt-4o"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4O_EXTENDED"] = "openai/gpt-4o:extended"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_70B_INSTRUCT"] = "meta-llama/llama-3-70b-instruct"; + E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_8B_INSTRUCT"] = "meta-llama/llama-3-8b-instruct"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MIXTRAL_8X22B_INSTRUCT"] = "mistralai/mixtral-8x22b-instruct"; E_OPENROUTER_MODEL["MODEL_MICROSOFT_WIZARDLM_2_8X22B"] = "microsoft/wizardlm-2-8x22b"; - E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_PRO_1_5"] = "google/gemini-pro-1.5"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4_TURBO"] = "openai/gpt-4-turbo"; - E_OPENROUTER_MODEL["MODEL_COHERE_COMMAND_R_PLUS"] = "cohere/command-r-plus"; - E_OPENROUTER_MODEL["MODEL_COHERE_COMMAND_R_PLUS_04_2024"] = "cohere/command-r-plus-04-2024"; - E_OPENROUTER_MODEL["MODEL_COHERE_COMMAND"] = "cohere/command"; - E_OPENROUTER_MODEL["MODEL_COHERE_COMMAND_R"] = "cohere/command-r"; E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_3_HAIKU"] = "anthropic/claude-3-haiku"; E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_3_OPUS"] = "anthropic/claude-3-opus"; - E_OPENROUTER_MODEL["MODEL_COHERE_COMMAND_R_03_2024"] = "cohere/command-r-03-2024"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_LARGE"] = "mistralai/mistral-large"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_3_5_TURBO_0613"] = "openai/gpt-3.5-turbo-0613"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4_TURBO_PREVIEW"] = "openai/gpt-4-turbo-preview"; - E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_SMALL"] = "mistralai/mistral-small"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_TINY"] = "mistralai/mistral-tiny"; + E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_7B_INSTRUCT_V0_2"] = "mistralai/mistral-7b-instruct-v0.2"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MIXTRAL_8X7B_INSTRUCT"] = "mistralai/mixtral-8x7b-instruct"; E_OPENROUTER_MODEL["MODEL_NEVERSLEEP_NOROMAID_20B"] = "neversleep/noromaid-20b"; E_OPENROUTER_MODEL["MODEL_ALPINDALE_GOLIATH_120B"] = "alpindale/goliath-120b"; @@ -324,8 +350,8 @@ export var E_OPENROUTER_MODEL; E_OPENROUTER_MODEL["MODEL_MANCER_WEAVER"] = "mancer/weaver"; E_OPENROUTER_MODEL["MODEL_UNDI95_REMM_SLERP_L2_13B"] = "undi95/remm-slerp-l2-13b"; E_OPENROUTER_MODEL["MODEL_GRYPHE_MYTHOMAX_L2_13B"] = "gryphe/mythomax-l2-13b"; - E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_3_5_TURBO"] = "openai/gpt-3.5-turbo"; - E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4"] = "openai/gpt-4"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4_0314"] = "openai/gpt-4-0314"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4"] = "openai/gpt-4"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_3_5_TURBO"] = "openai/gpt-3.5-turbo"; })(E_OPENROUTER_MODEL || (E_OPENROUTER_MODEL = {})); -//# 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\ No newline at end of file diff --git a/packages/kbot/dist-in/src/models/cache/openai.ts b/packages/kbot/dist-in/src/models/cache/openai.ts index 903d9e9c..456bde1c 100644 --- a/packages/kbot/dist-in/src/models/cache/openai.ts +++ b/packages/kbot/dist-in/src/models/cache/openai.ts @@ -1 +1 @@ -export const models = 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\ No newline at end of file +export const models = [{"id":"gpt-4-0613","object":"model","created":1686588896,"owned_by":"openai"},{"id":"gpt-4","object":"model","created":1687882411,"owned_by":"openai"},{"id":"gpt-3.5-turbo","object":"model","created":1677610602,"owned_by":"openai"},{"id":"gpt-5.2-codex","object":"model","created":1766164985,"owned_by":"system"},{"id":"gpt-4o-mini-tts-2025-12-15","object":"model","created":1765610837,"owned_by":"system"},{"id":"gpt-realtime-mini-2025-12-15","object":"model","created":1765612007,"owned_by":"system"},{"id":"gpt-audio-mini-2025-12-15","object":"model","created":1765760008,"owned_by":"system"},{"id":"chatgpt-image-latest","object":"model","created":1765925279,"owned_by":"system"},{"id":"davinci-002","object":"model","created":1692634301,"owned_by":"system"},{"id":"babbage-002","object":"model","created":1692634615,"owned_by":"system"},{"id":"gpt-3.5-turbo-instruct","object":"model","created":1692901427,"owned_by":"system"},{"id":"gpt-3.5-turbo-instruct-0914","object":"model","created":1694122472,"owned_by":"system"},{"id":"dall-e-3","object":"model","created":1698785189,"owned_by":"system"},{"id":"dall-e-2","object":"model","created":1698798177,"owned_by":"system"},{"id":"gpt-4-1106-preview","object":"model","created":1698957206,"owned_by":"system"},{"id":"gpt-3.5-turbo-1106","object":"model","created":1698959748,"owned_by":"system"},{"id":"tts-1-hd","object":"model","created":1699046015,"owned_by":"system"},{"id":"tts-1-1106","object":"model","created":1699053241,"owned_by":"system"},{"id":"tts-1-hd-1106","object":"model","created":1699053533,"owned_by":"system"},{"id":"text-embedding-3-small","object":"model","created":1705948997,"owned_by":"system"},{"id":"text-embedding-3-large","object":"model","created":1705953180,"owned_by":"system"},{"id":"gpt-4-0125-preview","object":"model","created":1706037612,"owned_by":"system"},{"id":"gpt-4-turbo-preview","object":"model","created":1706037777,"owned_by":"system"},{"id":"gpt-3.5-turbo-0125","object":"model","created":1706048358,"owned_by":"system"},{"id":"gpt-4-turbo","object":"model","created":1712361441,"owned_by":"system"},{"id":"gpt-4-turbo-2024-04-09","object":"model","created":1712601677,"owned_by":"system"},{"id":"gpt-4o","object":"model","created":1715367049,"owned_by":"system"},{"id":"gpt-4o-2024-05-13","object":"model","created":1715368132,"owned_by":"system"},{"id":"gpt-4o-mini-2024-07-18","object":"model","created":1721172717,"owned_by":"system"},{"id":"gpt-4o-mini","object":"model","created":1721172741,"owned_by":"system"},{"id":"gpt-4o-2024-08-06","object":"model","created":1722814719,"owned_by":"system"},{"id":"chatgpt-4o-latest","object":"model","created":1723515131,"owned_by":"system"},{"id":"gpt-4o-audio-preview","object":"model","created":1727460443,"owned_by":"system"},{"id":"gpt-4o-realtime-preview","object":"model","created":1727659998,"owned_by":"system"},{"id":"omni-moderation-latest","object":"model","created":1731689265,"owned_by":"system"},{"id":"omni-moderation-2024-09-26","object":"model","created":1732734466,"owned_by":"system"},{"id":"gpt-4o-realtime-preview-2024-12-17","object":"model","created":1733945430,"owned_by":"system"},{"id":"gpt-4o-audio-preview-2024-12-17","object":"model","created":1734034239,"owned_by":"system"},{"id":"gpt-4o-mini-realtime-preview-2024-12-17","object":"model","created":1734112601,"owned_by":"system"},{"id":"gpt-4o-mini-audio-preview-2024-12-17","object":"model","created":1734115920,"owned_by":"system"},{"id":"o1-2024-12-17","object":"model","created":1734326976,"owned_by":"system"},{"id":"o1","object":"model","created":1734375816,"owned_by":"system"},{"id":"gpt-4o-mini-realtime-preview","object":"model","created":1734387380,"owned_by":"system"},{"id":"gpt-4o-mini-audio-preview","object":"model","created":1734387424,"owned_by":"system"},{"id":"o3-mini","object":"model","created":1737146383,"owned_by":"system"},{"id":"o3-mini-2025-01-31","object":"model","created":1738010200,"owned_by":"system"},{"id":"gpt-4o-2024-11-20","object":"model","created":1739331543,"owned_by":"system"},{"id":"gpt-4o-search-preview-2025-03-11","object":"model","created":1741388170,"owned_by":"system"},{"id":"gpt-4o-search-preview","object":"model","created":1741388720,"owned_by":"system"},{"id":"gpt-4o-mini-search-preview-2025-03-11","object":"model","created":1741390858,"owned_by":"system"},{"id":"gpt-4o-mini-search-preview","object":"model","created":1741391161,"owned_by":"system"},{"id":"gpt-4o-transcribe","object":"model","created":1742068463,"owned_by":"system"},{"id":"gpt-4o-mini-transcribe","object":"model","created":1742068596,"owned_by":"system"},{"id":"o1-pro-2025-03-19","object":"model","created":1742251504,"owned_by":"system"},{"id":"o1-pro","object":"model","created":1742251791,"owned_by":"system"},{"id":"gpt-4o-mini-tts","object":"model","created":1742403959,"owned_by":"system"},{"id":"o3-2025-04-16","object":"model","created":1744133301,"owned_by":"system"},{"id":"o4-mini-2025-04-16","object":"model","created":174413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Turbo","pricing":{"prompt":"0.0000005","completion":"0.0000015"},"created":1685232000,"top_provider":{"context_length":16385,"max_completion_tokens":4096,"is_moderated":true}}] \ No newline at end of file diff --git a/packages/kbot/dist-in/zod_types.d.ts b/packages/kbot/dist-in/zod_types.d.ts index 98979c03..dd640f22 100644 --- a/packages/kbot/dist-in/zod_types.d.ts +++ b/packages/kbot/dist-in/zod_types.d.ts @@ -31,95 +31,95 @@ export interface IKBotOptions {   OpenRouter models:  - agentica-org/deepcoder-14b-preview | paid - agentica-org/deepcoder-14b-preview:free | free ai21/jamba-large-1.7 | paid ai21/jamba-mini-1.7 | paid aion-labs/aion-1.0 | paid aion-labs/aion-1.0-mini | paid aion-labs/aion-rp-llama-3.1-8b | paid alfredpros/codellama-7b-instruct-solidity | paid - allenai/molmo-7b-d | paid allenai/olmo-2-0325-32b-instruct | paid + allenai/olmo-3-32b-think:free | free + allenai/olmo-3-7b-instruct | paid + allenai/olmo-3-7b-think | paid + allenai/olmo-3.1-32b-think:free | free + amazon/nova-2-lite-v1 | paid amazon/nova-lite-v1 | paid amazon/nova-micro-v1 | paid + amazon/nova-premier-v1 | paid amazon/nova-pro-v1 | paid anthropic/claude-3-haiku | paid anthropic/claude-3-opus | paid anthropic/claude-3.5-haiku | paid anthropic/claude-3.5-haiku-20241022 | paid anthropic/claude-3.5-sonnet | paid - anthropic/claude-3.5-sonnet-20240620 | paid anthropic/claude-3.7-sonnet | paid anthropic/claude-3.7-sonnet:thinking | paid + anthropic/claude-haiku-4.5 | paid anthropic/claude-opus-4 | paid anthropic/claude-opus-4.1 | paid + anthropic/claude-opus-4.5 | paid anthropic/claude-sonnet-4 | paid - arcee-ai/afm-4.5b | paid + anthropic/claude-sonnet-4.5 | paid arcee-ai/coder-large | paid arcee-ai/maestro-reasoning | paid arcee-ai/spotlight | paid + arcee-ai/trinity-mini | paid + arcee-ai/trinity-mini:free | free arcee-ai/virtuoso-large | paid arliai/qwq-32b-arliai-rpr-v1 | paid - arliai/qwq-32b-arliai-rpr-v1:free | free openrouter/auto | paid baidu/ernie-4.5-21b-a3b | paid + baidu/ernie-4.5-21b-a3b-thinking | paid baidu/ernie-4.5-300b-a47b | paid baidu/ernie-4.5-vl-28b-a3b | paid baidu/ernie-4.5-vl-424b-a47b | paid - bytedance/seed-oss-36b-instruct | paid + openrouter/bodybuilder | paid + bytedance-seed/seed-1.6 | paid + bytedance-seed/seed-1.6-flash | paid bytedance/ui-tars-1.5-7b | paid deepcogito/cogito-v2-preview-llama-109b-moe | paid - cohere/command | paid cohere/command-a | paid - cohere/command-r | paid - cohere/command-r-03-2024 | paid cohere/command-r-08-2024 | paid - cohere/command-r-plus | paid - cohere/command-r-plus-04-2024 | paid cohere/command-r-plus-08-2024 | paid cohere/command-r7b-12-2024 | paid - deepcogito/cogito-v2-preview-deepseek-671b | paid + deepcogito/cogito-v2-preview-llama-405b | paid + deepcogito/cogito-v2-preview-llama-70b | paid + deepcogito/cogito-v2.1-671b | paid deepseek/deepseek-prover-v2 | paid deepseek/deepseek-r1-0528-qwen3-8b | paid - deepseek/deepseek-r1-0528-qwen3-8b:free | free deepseek/deepseek-chat | paid deepseek/deepseek-chat-v3-0324 | paid - deepseek/deepseek-chat-v3-0324:free | free deepseek/deepseek-chat-v3.1 | paid - deepseek/deepseek-chat-v3.1:free | free - deepseek/deepseek-v3.1-base | paid + deepseek/deepseek-v3.1-terminus | paid + deepseek/deepseek-v3.1-terminus:exacto | paid + deepseek/deepseek-v3.2 | paid + deepseek/deepseek-v3.2-exp | paid + deepseek/deepseek-v3.2-speciale | paid deepseek/deepseek-r1 | paid - deepseek/deepseek-r1:free | free deepseek/deepseek-r1-0528 | paid deepseek/deepseek-r1-0528:free | free deepseek/deepseek-r1-distill-llama-70b | paid - deepseek/deepseek-r1-distill-llama-70b:free | free - deepseek/deepseek-r1-distill-llama-8b | paid deepseek/deepseek-r1-distill-qwen-14b | paid deepseek/deepseek-r1-distill-qwen-32b | paid - cognitivecomputations/dolphin3.0-mistral-24b | paid - cognitivecomputations/dolphin3.0-mistral-24b:free | free - cognitivecomputations/dolphin3.0-r1-mistral-24b | paid - cognitivecomputations/dolphin3.0-r1-mistral-24b:free | free eleutherai/llemma_7b | paid + essentialai/rnj-1-instruct | paid alpindale/goliath-120b | paid - google/gemini-flash-1.5 | paid - google/gemini-flash-1.5-8b | paid - google/gemini-pro-1.5 | paid google/gemini-2.0-flash-001 | paid google/gemini-2.0-flash-exp:free | free google/gemini-2.0-flash-lite-001 | paid google/gemini-2.5-flash | paid + google/gemini-2.5-flash-image | paid google/gemini-2.5-flash-image-preview | paid google/gemini-2.5-flash-lite | paid - google/gemini-2.5-flash-lite-preview-06-17 | paid + google/gemini-2.5-flash-lite-preview-09-2025 | paid + google/gemini-2.5-flash-preview-09-2025 | paid google/gemini-2.5-pro | paid google/gemini-2.5-pro-preview-05-06 | paid google/gemini-2.5-pro-preview | paid + google/gemini-3-flash-preview | paid + google/gemini-3-pro-preview | paid google/gemma-2-27b-it | paid google/gemma-2-9b-it | paid - google/gemma-2-9b-it:free | free google/gemma-3-12b-it | paid google/gemma-3-12b-it:free | free google/gemma-3-27b-it | paid @@ -129,14 +129,16 @@ export interface IKBotOptions { google/gemma-3n-e2b-it:free | free google/gemma-3n-e4b-it | paid google/gemma-3n-e4b-it:free | free + google/gemini-3-pro-image-preview | paid + ibm-granite/granite-4.0-h-micro | paid inception/mercury | paid inception/mercury-coder | paid inflection/inflection-3-pi | paid inflection/inflection-3-productivity | paid - liquid/lfm-3b | paid - liquid/lfm-7b | paid + kwaipilot/kat-coder-pro:free | free + liquid/lfm-2.2-6b | paid + liquid/lfm2-8b-a1b | paid meta-llama/llama-guard-3-8b | paid - anthracite-org/magnum-v2-72b | paid anthracite-org/magnum-v4-72b | paid mancer/weaver | paid meituan/longcat-flash-chat | paid @@ -154,15 +156,10 @@ export interface IKBotOptions { meta-llama/llama-3.2-90b-vision-instruct | paid meta-llama/llama-3.3-70b-instruct | paid meta-llama/llama-3.3-70b-instruct:free | free - meta-llama/llama-3.3-8b-instruct:free | free meta-llama/llama-4-maverick | paid - meta-llama/llama-4-maverick:free | free meta-llama/llama-4-scout | paid - meta-llama/llama-4-scout:free | free meta-llama/llama-guard-4-12b | paid meta-llama/llama-guard-2-8b | paid - microsoft/mai-ds-r1 | paid - microsoft/mai-ds-r1:free | free microsoft/phi-4 | paid microsoft/phi-4-multimodal-instruct | paid microsoft/phi-4-reasoning-plus | paid @@ -170,64 +167,70 @@ export interface IKBotOptions { microsoft/phi-3-mini-128k-instruct | paid microsoft/phi-3.5-mini-128k-instruct | paid minimax/minimax-m1 | paid + minimax/minimax-m2 | paid + minimax/minimax-m2.1 | paid minimax/minimax-01 | paid mistralai/mistral-large | paid mistralai/mistral-large-2407 | paid mistralai/mistral-large-2411 | paid - mistralai/mistral-small | paid mistralai/mistral-tiny | paid - mistralai/codestral-2501 | paid mistralai/codestral-2508 | paid + mistralai/devstral-2512 | paid + mistralai/devstral-2512:free | free mistralai/devstral-medium | paid mistralai/devstral-small | paid mistralai/devstral-small-2505 | paid - mistralai/devstral-small-2505:free | free - mistralai/magistral-medium-2506 | paid - mistralai/magistral-medium-2506:thinking | paid - mistralai/magistral-small-2506 | paid + mistralai/ministral-14b-2512 | paid + mistralai/ministral-3b-2512 | paid + mistralai/ministral-8b-2512 | paid mistralai/ministral-3b | paid mistralai/ministral-8b | paid mistralai/mistral-7b-instruct | paid mistralai/mistral-7b-instruct:free | free mistralai/mistral-7b-instruct-v0.1 | paid + mistralai/mistral-7b-instruct-v0.2 | paid mistralai/mistral-7b-instruct-v0.3 | paid + mistralai/mistral-large-2512 | paid mistralai/mistral-medium-3 | paid mistralai/mistral-medium-3.1 | paid mistralai/mistral-nemo | paid - mistralai/mistral-nemo:free | free mistralai/mistral-small-24b-instruct-2501 | paid - mistralai/mistral-small-24b-instruct-2501:free | free mistralai/mistral-small-3.1-24b-instruct | paid mistralai/mistral-small-3.1-24b-instruct:free | free mistralai/mistral-small-3.2-24b-instruct | paid - mistralai/mistral-small-3.2-24b-instruct:free | free + mistralai/mistral-small-creative | paid mistralai/mixtral-8x22b-instruct | paid mistralai/mixtral-8x7b-instruct | paid mistralai/pixtral-12b | paid mistralai/pixtral-large-2411 | paid mistralai/mistral-saba | paid + mistralai/voxtral-small-24b-2507 | paid moonshotai/kimi-dev-72b | paid - moonshotai/kimi-dev-72b:free | free moonshotai/kimi-k2 | paid moonshotai/kimi-k2:free | free moonshotai/kimi-k2-0905 | paid - moonshotai/kimi-vl-a3b-thinking | paid - moonshotai/kimi-vl-a3b-thinking:free | free + moonshotai/kimi-k2-0905:exacto | paid + moonshotai/kimi-k2-thinking | paid morph/morph-v3-fast | paid morph/morph-v3-large | paid gryphe/mythomax-l2-13b | paid - neversleep/llama-3-lumimaid-70b | paid neversleep/llama-3.1-lumimaid-8b | paid + nex-agi/deepseek-v3.1-nex-n1:free | free neversleep/noromaid-20b | paid - nousresearch/deephermes-3-llama-3-8b-preview:free | free nousresearch/deephermes-3-mistral-24b-preview | paid nousresearch/hermes-3-llama-3.1-405b | paid + nousresearch/hermes-3-llama-3.1-405b:free | free nousresearch/hermes-3-llama-3.1-70b | paid nousresearch/hermes-4-405b | paid nousresearch/hermes-4-70b | paid nousresearch/hermes-2-pro-llama-3-8b | paid nvidia/llama-3.1-nemotron-70b-instruct | paid nvidia/llama-3.1-nemotron-ultra-253b-v1 | paid + nvidia/llama-3.3-nemotron-super-49b-v1.5 | paid + nvidia/nemotron-3-nano-30b-a3b | paid + nvidia/nemotron-3-nano-30b-a3b:free | free + nvidia/nemotron-nano-12b-v2-vl | paid + nvidia/nemotron-nano-12b-v2-vl:free | free nvidia/nemotron-nano-9b-v2 | paid nvidia/nemotron-nano-9b-v2:free | free openai/chatgpt-4o-latest | paid @@ -256,29 +259,44 @@ export interface IKBotOptions { openai/gpt-4o-mini-search-preview | paid openai/gpt-5 | paid openai/gpt-5-chat | paid + openai/gpt-5-codex | paid + openai/gpt-5-image | paid + openai/gpt-5-image-mini | paid openai/gpt-5-mini | paid openai/gpt-5-nano | paid + openai/gpt-5-pro | paid + openai/gpt-5.1 | paid + openai/gpt-5.1-chat | paid + openai/gpt-5.1-codex | paid + openai/gpt-5.1-codex-max | paid + openai/gpt-5.1-codex-mini | paid + openai/gpt-5.2 | paid + openai/gpt-5.2-chat | paid + openai/gpt-5.2-pro | paid openai/gpt-oss-120b | paid + openai/gpt-oss-120b:exacto | paid openai/gpt-oss-120b:free | free openai/gpt-oss-20b | paid openai/gpt-oss-20b:free | free + openai/gpt-oss-safeguard-20b | paid openai/o1 | paid - openai/o1-mini | paid - openai/o1-mini-2024-09-12 | paid openai/o1-pro | paid openai/o3 | paid + openai/o3-deep-research | paid openai/o3-mini | paid openai/o3-mini-high | paid openai/o3-pro | paid openai/o4-mini | paid + openai/o4-mini-deep-research | paid openai/o4-mini-high | paid opengvlab/internvl3-78b | paid - perplexity/r1-1776 | paid perplexity/sonar | paid perplexity/sonar-deep-research | paid perplexity/sonar-pro | paid + perplexity/sonar-pro-search | paid perplexity/sonar-reasoning | paid perplexity/sonar-reasoning-pro | paid + prime-intellect/intellect-3 | paid qwen/qwen-plus-2025-07-28 | paid qwen/qwen-plus-2025-07-28:thinking | paid qwen/qwen-vl-max | paid @@ -286,64 +304,66 @@ export interface IKBotOptions { qwen/qwen-max | paid qwen/qwen-plus | paid qwen/qwen-turbo | paid + qwen/qwen-2.5-7b-instruct | paid + qwen/qwen2.5-coder-7b-instruct | paid qwen/qwen2.5-vl-32b-instruct | paid - qwen/qwen2.5-vl-32b-instruct:free | free qwen/qwen2.5-vl-72b-instruct | paid - qwen/qwen2.5-vl-72b-instruct:free | free qwen/qwen-2.5-vl-7b-instruct | paid + qwen/qwen-2.5-vl-7b-instruct:free | free qwen/qwen3-14b | paid - qwen/qwen3-14b:free | free qwen/qwen3-235b-a22b | paid - qwen/qwen3-235b-a22b:free | free qwen/qwen3-235b-a22b-2507 | paid qwen/qwen3-235b-a22b-thinking-2507 | paid qwen/qwen3-30b-a3b | paid - qwen/qwen3-30b-a3b:free | free qwen/qwen3-30b-a3b-instruct-2507 | paid qwen/qwen3-30b-a3b-thinking-2507 | paid qwen/qwen3-32b | paid qwen/qwen3-4b:free | free qwen/qwen3-8b | paid - qwen/qwen3-8b:free | free qwen/qwen3-coder-30b-a3b-instruct | paid qwen/qwen3-coder | paid + qwen/qwen3-coder:exacto | paid qwen/qwen3-coder:free | free qwen/qwen3-coder-flash | paid qwen/qwen3-coder-plus | paid qwen/qwen3-max | paid qwen/qwen3-next-80b-a3b-instruct | paid qwen/qwen3-next-80b-a3b-thinking | paid + qwen/qwen3-vl-235b-a22b-instruct | paid + qwen/qwen3-vl-235b-a22b-thinking | paid + qwen/qwen3-vl-30b-a3b-instruct | paid + qwen/qwen3-vl-30b-a3b-thinking | paid + qwen/qwen3-vl-32b-instruct | paid + qwen/qwen3-vl-8b-instruct | paid + qwen/qwen3-vl-8b-thinking | paid qwen/qwq-32b | paid - qwen/qwq-32b:free | free - qwen/qwq-32b-preview | paid qwen/qwen-2.5-72b-instruct | paid - qwen/qwen-2.5-72b-instruct:free | free - qwen/qwen-2.5-7b-instruct | paid qwen/qwen-2.5-coder-32b-instruct | paid - qwen/qwen-2.5-coder-32b-instruct:free | free + relace/relace-apply-3 | paid + relace/relace-search | paid undi95/remm-slerp-l2-13b | paid sao10k/l3-lunaris-8b | paid sao10k/l3-euryale-70b | paid + sao10k/l3.1-70b-hanami-x1 | paid sao10k/l3.1-euryale-70b | paid sao10k/l3.3-euryale-70b | paid - shisa-ai/shisa-v2-llama3.3-70b | paid - shisa-ai/shisa-v2-llama3.3-70b:free | free raifle/sorcererlm-8x22b | paid stepfun-ai/step3 | paid switchpoint/router | paid tencent/hunyuan-a13b-instruct | paid - tencent/hunyuan-a13b-instruct:free | free - thedrummer/anubis-70b-v1.1 | paid - thedrummer/anubis-pro-105b-v1 | paid + thedrummer/cydonia-24b-v4.1 | paid thedrummer/rocinante-12b | paid thedrummer/skyfall-36b-v2 | paid thedrummer/unslopnemo-12b | paid thudm/glm-4.1v-9b-thinking | paid - thudm/glm-z1-32b | paid tngtech/deepseek-r1t-chimera | paid tngtech/deepseek-r1t-chimera:free | free + tngtech/deepseek-r1t2-chimera | paid tngtech/deepseek-r1t2-chimera:free | free + tngtech/tng-r1t-chimera | paid + tngtech/tng-r1t-chimera:free | free alibaba/tongyi-deepresearch-30b-a3b | paid + alibaba/tongyi-deepresearch-30b-a3b:free | free cognitivecomputations/dolphin-mistral-24b-venice-edition:free | free microsoft/wizardlm-2-8x22b | paid x-ai/grok-3 | paid @@ -351,18 +371,25 @@ export interface IKBotOptions { x-ai/grok-3-mini | paid x-ai/grok-3-mini-beta | paid x-ai/grok-4 | paid - x-ai/grok-4-fast:free | free + x-ai/grok-4-fast | paid + x-ai/grok-4.1-fast | paid x-ai/grok-code-fast-1 | paid + xiaomi/mimo-v2-flash:free | free z-ai/glm-4-32b | paid z-ai/glm-4.5 | paid z-ai/glm-4.5-air | paid z-ai/glm-4.5-air:free | free z-ai/glm-4.5v | paid + z-ai/glm-4.6 | paid + z-ai/glm-4.6:exacto | paid + z-ai/glm-4.6v | paid + z-ai/glm-4.7 | paid   OpenAI models:  babbage-002 chatgpt-4o-latest + chatgpt-image-latest codex-mini-latest dall-e-2 dall-e-3 @@ -391,7 +418,6 @@ export interface IKBotOptions { gpt-4o-2024-08-06 gpt-4o-2024-11-20 gpt-4o-audio-preview - gpt-4o-audio-preview-2024-10-01 gpt-4o-audio-preview-2024-12-17 gpt-4o-audio-preview-2025-06-03 gpt-4o-mini @@ -403,30 +429,56 @@ export interface IKBotOptions { gpt-4o-mini-search-preview gpt-4o-mini-search-preview-2025-03-11 gpt-4o-mini-transcribe + gpt-4o-mini-transcribe-2025-03-20 + gpt-4o-mini-transcribe-2025-12-15 gpt-4o-mini-tts + gpt-4o-mini-tts-2025-03-20 + gpt-4o-mini-tts-2025-12-15 gpt-4o-realtime-preview - gpt-4o-realtime-preview-2024-10-01 gpt-4o-realtime-preview-2024-12-17 gpt-4o-realtime-preview-2025-06-03 gpt-4o-search-preview gpt-4o-search-preview-2025-03-11 gpt-4o-transcribe + gpt-4o-transcribe-diarize gpt-5 gpt-5-2025-08-07 gpt-5-chat-latest + gpt-5-codex gpt-5-mini gpt-5-mini-2025-08-07 gpt-5-nano gpt-5-nano-2025-08-07 + gpt-5-pro + gpt-5-pro-2025-10-06 + gpt-5-search-api + gpt-5-search-api-2025-10-14 + gpt-5.1 + gpt-5.1-2025-11-13 + gpt-5.1-chat-latest + gpt-5.1-codex + gpt-5.1-codex-max + gpt-5.1-codex-mini + gpt-5.2 + gpt-5.2-2025-12-11 + gpt-5.2-chat-latest + gpt-5.2-pro + gpt-5.2-pro-2025-12-11 gpt-audio gpt-audio-2025-08-28 + gpt-audio-mini + gpt-audio-mini-2025-10-06 + gpt-audio-mini-2025-12-15 gpt-image-1 + gpt-image-1-mini + gpt-image-1.5 gpt-realtime gpt-realtime-2025-08-28 + gpt-realtime-mini + gpt-realtime-mini-2025-10-06 + gpt-realtime-mini-2025-12-15 o1 o1-2024-12-17 - o1-mini - o1-mini-2024-09-12 o1-pro o1-pro-2025-03-19 o3 @@ -439,6 +491,8 @@ export interface IKBotOptions { o4-mini-deep-research-2025-06-26 omni-moderation-2024-09-26 omni-moderation-latest + sora-2 + sora-2-pro text-embedding-3-large text-embedding-3-small text-embedding-ada-002 diff --git a/packages/kbot/dist/main_node.js b/packages/kbot/dist/main_node.js index 61a7510d..84847cd0 100644 --- a/packages/kbot/dist/main_node.js +++ b/packages/kbot/dist/main_node.js @@ -257131,11 +257131,11 @@ var E_OPENAI_MODEL; E_OPENAI_MODEL["MODEL_GPT_4_0613"] = "gpt-4-0613"; E_OPENAI_MODEL["MODEL_GPT_4"] = "gpt-4"; E_OPENAI_MODEL["MODEL_GPT_3_5_TURBO"] = "gpt-3.5-turbo"; - E_OPENAI_MODEL["MODEL_GPT_AUDIO"] = "gpt-audio"; - E_OPENAI_MODEL["MODEL_GPT_5_NANO"] = "gpt-5-nano"; - E_OPENAI_MODEL["MODEL_GPT_AUDIO_2025_08_28"] = "gpt-audio-2025-08-28"; - E_OPENAI_MODEL["MODEL_GPT_REALTIME"] = "gpt-realtime"; - E_OPENAI_MODEL["MODEL_GPT_REALTIME_2025_08_28"] = "gpt-realtime-2025-08-28"; + E_OPENAI_MODEL["MODEL_CHATGPT_IMAGE_LATEST"] = "chatgpt-image-latest"; + E_OPENAI_MODEL["MODEL_GPT_4O_MINI_TTS_2025_03_20"] = "gpt-4o-mini-tts-2025-03-20"; + E_OPENAI_MODEL["MODEL_GPT_4O_MINI_TTS_2025_12_15"] = "gpt-4o-mini-tts-2025-12-15"; + E_OPENAI_MODEL["MODEL_GPT_REALTIME_MINI_2025_12_15"] = "gpt-realtime-mini-2025-12-15"; + E_OPENAI_MODEL["MODEL_GPT_AUDIO_MINI_2025_12_15"] = "gpt-audio-mini-2025-12-15"; E_OPENAI_MODEL["MODEL_DAVINCI_002"] = "davinci-002"; E_OPENAI_MODEL["MODEL_BABBAGE_002"] = "babbage-002"; E_OPENAI_MODEL["MODEL_GPT_3_5_TURBO_INSTRUCT"] = "gpt-3.5-turbo-instruct"; @@ -257160,10 +257160,6 @@ var E_OPENAI_MODEL; E_OPENAI_MODEL["MODEL_GPT_4O_MINI"] = "gpt-4o-mini"; E_OPENAI_MODEL["MODEL_GPT_4O_2024_08_06"] = "gpt-4o-2024-08-06"; E_OPENAI_MODEL["MODEL_CHATGPT_4O_LATEST"] = "chatgpt-4o-latest"; - E_OPENAI_MODEL["MODEL_O1_MINI_2024_09_12"] = "o1-mini-2024-09-12"; - E_OPENAI_MODEL["MODEL_O1_MINI"] = "o1-mini"; - E_OPENAI_MODEL["MODEL_GPT_4O_REALTIME_PREVIEW_2024_10_01"] = "gpt-4o-realtime-preview-2024-10-01"; - E_OPENAI_MODEL["MODEL_GPT_4O_AUDIO_PREVIEW_2024_10_01"] = "gpt-4o-audio-preview-2024-10-01"; E_OPENAI_MODEL["MODEL_GPT_4O_AUDIO_PREVIEW"] = "gpt-4o-audio-preview"; E_OPENAI_MODEL["MODEL_GPT_4O_REALTIME_PREVIEW"] = "gpt-4o-realtime-preview"; E_OPENAI_MODEL["MODEL_OMNI_MODERATION_LATEST"] = "omni-moderation-latest"; @@ -257203,6 +257199,7 @@ var E_OPENAI_MODEL; E_OPENAI_MODEL["MODEL_GPT_4O_REALTIME_PREVIEW_2025_06_03"] = "gpt-4o-realtime-preview-2025-06-03"; E_OPENAI_MODEL["MODEL_GPT_4O_AUDIO_PREVIEW_2025_06_03"] = "gpt-4o-audio-preview-2025-06-03"; E_OPENAI_MODEL["MODEL_O4_MINI_DEEP_RESEARCH"] = "o4-mini-deep-research"; + E_OPENAI_MODEL["MODEL_GPT_4O_TRANSCRIBE_DIARIZE"] = "gpt-4o-transcribe-diarize"; E_OPENAI_MODEL["MODEL_O4_MINI_DEEP_RESEARCH_2025_06_26"] = "o4-mini-deep-research-2025-06-26"; E_OPENAI_MODEL["MODEL_GPT_5_CHAT_LATEST"] = "gpt-5-chat-latest"; E_OPENAI_MODEL["MODEL_GPT_5_2025_08_07"] = "gpt-5-2025-08-07"; @@ -257210,20 +257207,137 @@ var E_OPENAI_MODEL; E_OPENAI_MODEL["MODEL_GPT_5_MINI_2025_08_07"] = "gpt-5-mini-2025-08-07"; E_OPENAI_MODEL["MODEL_GPT_5_MINI"] = "gpt-5-mini"; E_OPENAI_MODEL["MODEL_GPT_5_NANO_2025_08_07"] = "gpt-5-nano-2025-08-07"; + E_OPENAI_MODEL["MODEL_GPT_5_NANO"] = "gpt-5-nano"; + E_OPENAI_MODEL["MODEL_GPT_AUDIO_2025_08_28"] = "gpt-audio-2025-08-28"; + E_OPENAI_MODEL["MODEL_GPT_REALTIME"] = "gpt-realtime"; + E_OPENAI_MODEL["MODEL_GPT_REALTIME_2025_08_28"] = "gpt-realtime-2025-08-28"; + E_OPENAI_MODEL["MODEL_GPT_AUDIO"] = "gpt-audio"; + E_OPENAI_MODEL["MODEL_GPT_5_CODEX"] = "gpt-5-codex"; + E_OPENAI_MODEL["MODEL_GPT_IMAGE_1_MINI"] = "gpt-image-1-mini"; + E_OPENAI_MODEL["MODEL_GPT_5_PRO_2025_10_06"] = "gpt-5-pro-2025-10-06"; + E_OPENAI_MODEL["MODEL_GPT_5_PRO"] = "gpt-5-pro"; + E_OPENAI_MODEL["MODEL_GPT_AUDIO_MINI"] = "gpt-audio-mini"; + E_OPENAI_MODEL["MODEL_GPT_AUDIO_MINI_2025_10_06"] = "gpt-audio-mini-2025-10-06"; + E_OPENAI_MODEL["MODEL_GPT_5_SEARCH_API"] = "gpt-5-search-api"; + E_OPENAI_MODEL["MODEL_GPT_REALTIME_MINI"] = "gpt-realtime-mini"; + E_OPENAI_MODEL["MODEL_GPT_REALTIME_MINI_2025_10_06"] = "gpt-realtime-mini-2025-10-06"; + E_OPENAI_MODEL["MODEL_SORA_2"] = "sora-2"; + E_OPENAI_MODEL["MODEL_SORA_2_PRO"] = "sora-2-pro"; + E_OPENAI_MODEL["MODEL_GPT_5_SEARCH_API_2025_10_14"] = "gpt-5-search-api-2025-10-14"; + E_OPENAI_MODEL["MODEL_GPT_5_1_CHAT_LATEST"] = "gpt-5.1-chat-latest"; + E_OPENAI_MODEL["MODEL_GPT_5_1_2025_11_13"] = "gpt-5.1-2025-11-13"; + E_OPENAI_MODEL["MODEL_GPT_5_1"] = "gpt-5.1"; + E_OPENAI_MODEL["MODEL_GPT_5_1_CODEX"] = "gpt-5.1-codex"; + E_OPENAI_MODEL["MODEL_GPT_5_1_CODEX_MINI"] = "gpt-5.1-codex-mini"; + E_OPENAI_MODEL["MODEL_GPT_5_1_CODEX_MAX"] = "gpt-5.1-codex-max"; + E_OPENAI_MODEL["MODEL_GPT_IMAGE_1_5"] = "gpt-image-1.5"; + E_OPENAI_MODEL["MODEL_GPT_5_2_2025_12_11"] = "gpt-5.2-2025-12-11"; + E_OPENAI_MODEL["MODEL_GPT_5_2"] = "gpt-5.2"; + E_OPENAI_MODEL["MODEL_GPT_5_2_PRO_2025_12_11"] = "gpt-5.2-pro-2025-12-11"; + E_OPENAI_MODEL["MODEL_GPT_5_2_PRO"] = "gpt-5.2-pro"; + E_OPENAI_MODEL["MODEL_GPT_5_2_CHAT_LATEST"] = "gpt-5.2-chat-latest"; + E_OPENAI_MODEL["MODEL_GPT_4O_MINI_TRANSCRIBE_2025_12_15"] = "gpt-4o-mini-transcribe-2025-12-15"; + E_OPENAI_MODEL["MODEL_GPT_4O_MINI_TRANSCRIBE_2025_03_20"] = "gpt-4o-mini-transcribe-2025-03-20"; E_OPENAI_MODEL["MODEL_GPT_3_5_TURBO_16K"] = "gpt-3.5-turbo-16k"; E_OPENAI_MODEL["MODEL_TTS_1"] = "tts-1"; E_OPENAI_MODEL["MODEL_WHISPER_1"] = "whisper-1"; E_OPENAI_MODEL["MODEL_TEXT_EMBEDDING_ADA_002"] = "text-embedding-ada-002"; })(E_OPENAI_MODEL || (E_OPENAI_MODEL = {})); -//# 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+//# 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;// ./dist-in/models/cache/openrouter-models.js var E_OPENROUTER_MODEL; (function (E_OPENROUTER_MODEL) { - E_OPENROUTER_MODEL["MODEL_X_AI_GROK_4_FAST_FREE"] = "x-ai/grok-4-fast:free"; + E_OPENROUTER_MODEL["MODEL_BYTEDANCE_SEED_SEED_1_6_FLASH"] = "bytedance-seed/seed-1.6-flash"; + E_OPENROUTER_MODEL["MODEL_BYTEDANCE_SEED_SEED_1_6"] = "bytedance-seed/seed-1.6"; + E_OPENROUTER_MODEL["MODEL_MINIMAX_MINIMAX_M2_1"] = "minimax/minimax-m2.1"; + E_OPENROUTER_MODEL["MODEL_Z_AI_GLM_4_7"] = "z-ai/glm-4.7"; + E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_3_FLASH_PREVIEW"] = "google/gemini-3-flash-preview"; + E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_SMALL_CREATIVE"] = "mistralai/mistral-small-creative"; + E_OPENROUTER_MODEL["MODEL_ALLENAI_OLMO_3_1_32B_THINK_FREE"] = "allenai/olmo-3.1-32b-think:free"; + E_OPENROUTER_MODEL["MODEL_XIAOMI_MIMO_V2_FLASH_FREE"] = "xiaomi/mimo-v2-flash:free"; + E_OPENROUTER_MODEL["MODEL_NVIDIA_NEMOTRON_3_NANO_30B_A3B_FREE"] = "nvidia/nemotron-3-nano-30b-a3b:free"; + E_OPENROUTER_MODEL["MODEL_NVIDIA_NEMOTRON_3_NANO_30B_A3B"] = "nvidia/nemotron-3-nano-30b-a3b"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_5_2_CHAT"] = "openai/gpt-5.2-chat"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_5_2_PRO"] = "openai/gpt-5.2-pro"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_5_2"] = "openai/gpt-5.2"; + E_OPENROUTER_MODEL["MODEL_MISTRALAI_DEVSTRAL_2512_FREE"] = "mistralai/devstral-2512:free"; + E_OPENROUTER_MODEL["MODEL_MISTRALAI_DEVSTRAL_2512"] = "mistralai/devstral-2512"; + E_OPENROUTER_MODEL["MODEL_RELACE_RELACE_SEARCH"] = "relace/relace-search"; + E_OPENROUTER_MODEL["MODEL_Z_AI_GLM_4_6V"] = "z-ai/glm-4.6v"; + E_OPENROUTER_MODEL["MODEL_NEX_AGI_DEEPSEEK_V3_1_NEX_N1_FREE"] = "nex-agi/deepseek-v3.1-nex-n1:free"; + E_OPENROUTER_MODEL["MODEL_ESSENTIALAI_RNJ_1_INSTRUCT"] = "essentialai/rnj-1-instruct"; + E_OPENROUTER_MODEL["MODEL_OPENROUTER_BODYBUILDER"] = "openrouter/bodybuilder"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_5_1_CODEX_MAX"] = "openai/gpt-5.1-codex-max"; + E_OPENROUTER_MODEL["MODEL_AMAZON_NOVA_2_LITE_V1"] = "amazon/nova-2-lite-v1"; + E_OPENROUTER_MODEL["MODEL_MISTRALAI_MINISTRAL_14B_2512"] = "mistralai/ministral-14b-2512"; + E_OPENROUTER_MODEL["MODEL_MISTRALAI_MINISTRAL_8B_2512"] = "mistralai/ministral-8b-2512"; + E_OPENROUTER_MODEL["MODEL_MISTRALAI_MINISTRAL_3B_2512"] = "mistralai/ministral-3b-2512"; + E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_LARGE_2512"] = "mistralai/mistral-large-2512"; + E_OPENROUTER_MODEL["MODEL_ARCEE_AI_TRINITY_MINI_FREE"] = "arcee-ai/trinity-mini:free"; + E_OPENROUTER_MODEL["MODEL_ARCEE_AI_TRINITY_MINI"] = "arcee-ai/trinity-mini"; + E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_V3_2_SPECIALE"] = "deepseek/deepseek-v3.2-speciale"; + E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_V3_2"] = "deepseek/deepseek-v3.2"; + E_OPENROUTER_MODEL["MODEL_PRIME_INTELLECT_INTELLECT_3"] = "prime-intellect/intellect-3"; + E_OPENROUTER_MODEL["MODEL_TNGTECH_TNG_R1T_CHIMERA_FREE"] = "tngtech/tng-r1t-chimera:free"; + E_OPENROUTER_MODEL["MODEL_TNGTECH_TNG_R1T_CHIMERA"] = "tngtech/tng-r1t-chimera"; + E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_OPUS_4_5"] = "anthropic/claude-opus-4.5"; + E_OPENROUTER_MODEL["MODEL_ALLENAI_OLMO_3_32B_THINK_FREE"] = "allenai/olmo-3-32b-think:free"; + E_OPENROUTER_MODEL["MODEL_ALLENAI_OLMO_3_7B_INSTRUCT"] = "allenai/olmo-3-7b-instruct"; + E_OPENROUTER_MODEL["MODEL_ALLENAI_OLMO_3_7B_THINK"] = "allenai/olmo-3-7b-think"; + E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_3_PRO_IMAGE_PREVIEW"] = "google/gemini-3-pro-image-preview"; + E_OPENROUTER_MODEL["MODEL_X_AI_GROK_4_1_FAST"] = "x-ai/grok-4.1-fast"; + E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_3_PRO_PREVIEW"] = "google/gemini-3-pro-preview"; + E_OPENROUTER_MODEL["MODEL_DEEPCOGITO_COGITO_V2_1_671B"] = "deepcogito/cogito-v2.1-671b"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_5_1"] = "openai/gpt-5.1"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_5_1_CHAT"] = "openai/gpt-5.1-chat"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_5_1_CODEX"] = "openai/gpt-5.1-codex"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_5_1_CODEX_MINI"] = "openai/gpt-5.1-codex-mini"; + E_OPENROUTER_MODEL["MODEL_KWAIPILOT_KAT_CODER_PRO_FREE"] = "kwaipilot/kat-coder-pro:free"; + E_OPENROUTER_MODEL["MODEL_MOONSHOTAI_KIMI_K2_THINKING"] = "moonshotai/kimi-k2-thinking"; + E_OPENROUTER_MODEL["MODEL_AMAZON_NOVA_PREMIER_V1"] = "amazon/nova-premier-v1"; + E_OPENROUTER_MODEL["MODEL_PERPLEXITY_SONAR_PRO_SEARCH"] = "perplexity/sonar-pro-search"; + E_OPENROUTER_MODEL["MODEL_MISTRALAI_VOXTRAL_SMALL_24B_2507"] = "mistralai/voxtral-small-24b-2507"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_OSS_SAFEGUARD_20B"] = "openai/gpt-oss-safeguard-20b"; + E_OPENROUTER_MODEL["MODEL_NVIDIA_NEMOTRON_NANO_12B_V2_VL_FREE"] = "nvidia/nemotron-nano-12b-v2-vl:free"; + E_OPENROUTER_MODEL["MODEL_NVIDIA_NEMOTRON_NANO_12B_V2_VL"] = "nvidia/nemotron-nano-12b-v2-vl"; + E_OPENROUTER_MODEL["MODEL_MINIMAX_MINIMAX_M2"] = "minimax/minimax-m2"; + E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_VL_32B_INSTRUCT"] = "qwen/qwen3-vl-32b-instruct"; + E_OPENROUTER_MODEL["MODEL_LIQUID_LFM2_8B_A1B"] = "liquid/lfm2-8b-a1b"; + E_OPENROUTER_MODEL["MODEL_LIQUID_LFM_2_2_6B"] = "liquid/lfm-2.2-6b"; + E_OPENROUTER_MODEL["MODEL_IBM_GRANITE_GRANITE_4_0_H_MICRO"] = "ibm-granite/granite-4.0-h-micro"; + E_OPENROUTER_MODEL["MODEL_DEEPCOGITO_COGITO_V2_PREVIEW_LLAMA_405B"] = "deepcogito/cogito-v2-preview-llama-405b"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_5_IMAGE_MINI"] = "openai/gpt-5-image-mini"; + E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_HAIKU_4_5"] = "anthropic/claude-haiku-4.5"; + E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_VL_8B_THINKING"] = "qwen/qwen3-vl-8b-thinking"; + E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_VL_8B_INSTRUCT"] = "qwen/qwen3-vl-8b-instruct"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_5_IMAGE"] = "openai/gpt-5-image"; + E_OPENROUTER_MODEL["MODEL_OPENAI_O3_DEEP_RESEARCH"] = "openai/o3-deep-research"; + E_OPENROUTER_MODEL["MODEL_OPENAI_O4_MINI_DEEP_RESEARCH"] = "openai/o4-mini-deep-research"; + E_OPENROUTER_MODEL["MODEL_NVIDIA_LLAMA_3_3_NEMOTRON_SUPER_49B_V1_5"] = "nvidia/llama-3.3-nemotron-super-49b-v1.5"; + E_OPENROUTER_MODEL["MODEL_BAIDU_ERNIE_4_5_21B_A3B_THINKING"] = "baidu/ernie-4.5-21b-a3b-thinking"; + E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_2_5_FLASH_IMAGE"] = "google/gemini-2.5-flash-image"; + E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_VL_30B_A3B_THINKING"] = "qwen/qwen3-vl-30b-a3b-thinking"; + E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_VL_30B_A3B_INSTRUCT"] = "qwen/qwen3-vl-30b-a3b-instruct"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_5_PRO"] = "openai/gpt-5-pro"; + E_OPENROUTER_MODEL["MODEL_Z_AI_GLM_4_6"] = "z-ai/glm-4.6"; + E_OPENROUTER_MODEL["MODEL_Z_AI_GLM_4_6_EXACTO"] = "z-ai/glm-4.6:exacto"; + E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_SONNET_4_5"] = "anthropic/claude-sonnet-4.5"; + E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_V3_2_EXP"] = "deepseek/deepseek-v3.2-exp"; + E_OPENROUTER_MODEL["MODEL_THEDRUMMER_CYDONIA_24B_V4_1"] = "thedrummer/cydonia-24b-v4.1"; + E_OPENROUTER_MODEL["MODEL_RELACE_RELACE_APPLY_3"] = "relace/relace-apply-3"; + E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_2_5_FLASH_PREVIEW_09_2025"] = "google/gemini-2.5-flash-preview-09-2025"; + E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_2_5_FLASH_LITE_PREVIEW_09_2025"] = "google/gemini-2.5-flash-lite-preview-09-2025"; + E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_VL_235B_A22B_THINKING"] = "qwen/qwen3-vl-235b-a22b-thinking"; + E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_VL_235B_A22B_INSTRUCT"] = "qwen/qwen3-vl-235b-a22b-instruct"; + E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_MAX"] = "qwen/qwen3-max"; + E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_CODER_PLUS"] = "qwen/qwen3-coder-plus"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_5_CODEX"] = "openai/gpt-5-codex"; + E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_V3_1_TERMINUS_EXACTO"] = "deepseek/deepseek-v3.1-terminus:exacto"; + E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_V3_1_TERMINUS"] = "deepseek/deepseek-v3.1-terminus"; + E_OPENROUTER_MODEL["MODEL_X_AI_GROK_4_FAST"] = "x-ai/grok-4-fast"; + E_OPENROUTER_MODEL["MODEL_ALIBABA_TONGYI_DEEPRESEARCH_30B_A3B_FREE"] = "alibaba/tongyi-deepresearch-30b-a3b:free"; E_OPENROUTER_MODEL["MODEL_ALIBABA_TONGYI_DEEPRESEARCH_30B_A3B"] = "alibaba/tongyi-deepresearch-30b-a3b"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_CODER_FLASH"] = "qwen/qwen3-coder-flash"; - E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_CODER_PLUS"] = "qwen/qwen3-coder-plus"; - E_OPENROUTER_MODEL["MODEL_ARCEE_AI_AFM_4_5B"] = "arcee-ai/afm-4.5b"; E_OPENROUTER_MODEL["MODEL_OPENGVLAB_INTERNVL3_78B"] = "opengvlab/internvl3-78b"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_NEXT_80B_A3B_THINKING"] = "qwen/qwen3-next-80b-a3b-thinking"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_NEXT_80B_A3B_INSTRUCT"] = "qwen/qwen3-next-80b-a3b-instruct"; @@ -257232,20 +257346,17 @@ var E_OPENROUTER_MODEL; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN_PLUS_2025_07_28_THINKING"] = "qwen/qwen-plus-2025-07-28:thinking"; E_OPENROUTER_MODEL["MODEL_NVIDIA_NEMOTRON_NANO_9B_V2_FREE"] = "nvidia/nemotron-nano-9b-v2:free"; E_OPENROUTER_MODEL["MODEL_NVIDIA_NEMOTRON_NANO_9B_V2"] = "nvidia/nemotron-nano-9b-v2"; - E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_MAX"] = "qwen/qwen3-max"; E_OPENROUTER_MODEL["MODEL_MOONSHOTAI_KIMI_K2_0905"] = "moonshotai/kimi-k2-0905"; - E_OPENROUTER_MODEL["MODEL_BYTEDANCE_SEED_OSS_36B_INSTRUCT"] = "bytedance/seed-oss-36b-instruct"; + E_OPENROUTER_MODEL["MODEL_MOONSHOTAI_KIMI_K2_0905_EXACTO"] = "moonshotai/kimi-k2-0905:exacto"; + E_OPENROUTER_MODEL["MODEL_DEEPCOGITO_COGITO_V2_PREVIEW_LLAMA_70B"] = "deepcogito/cogito-v2-preview-llama-70b"; E_OPENROUTER_MODEL["MODEL_DEEPCOGITO_COGITO_V2_PREVIEW_LLAMA_109B_MOE"] = "deepcogito/cogito-v2-preview-llama-109b-moe"; - E_OPENROUTER_MODEL["MODEL_DEEPCOGITO_COGITO_V2_PREVIEW_DEEPSEEK_671B"] = "deepcogito/cogito-v2-preview-deepseek-671b"; E_OPENROUTER_MODEL["MODEL_STEPFUN_AI_STEP3"] = "stepfun-ai/step3"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_30B_A3B_THINKING_2507"] = "qwen/qwen3-30b-a3b-thinking-2507"; E_OPENROUTER_MODEL["MODEL_X_AI_GROK_CODE_FAST_1"] = "x-ai/grok-code-fast-1"; E_OPENROUTER_MODEL["MODEL_NOUSRESEARCH_HERMES_4_70B"] = "nousresearch/hermes-4-70b"; E_OPENROUTER_MODEL["MODEL_NOUSRESEARCH_HERMES_4_405B"] = "nousresearch/hermes-4-405b"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_2_5_FLASH_IMAGE_PREVIEW"] = "google/gemini-2.5-flash-image-preview"; - E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_CHAT_V3_1_FREE"] = "deepseek/deepseek-chat-v3.1:free"; E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_CHAT_V3_1"] = "deepseek/deepseek-chat-v3.1"; - E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_V3_1_BASE"] = "deepseek/deepseek-v3.1-base"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4O_AUDIO_PREVIEW"] = "openai/gpt-4o-audio-preview"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_MEDIUM_3_1"] = "mistralai/mistral-medium-3.1"; E_OPENROUTER_MODEL["MODEL_BAIDU_ERNIE_4_5_21B_A3B"] = "baidu/ernie-4.5-21b-a3b"; @@ -257259,6 +257370,7 @@ var E_OPENROUTER_MODEL; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_5_NANO"] = "openai/gpt-5-nano"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_OSS_120B_FREE"] = "openai/gpt-oss-120b:free"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_OSS_120B"] = "openai/gpt-oss-120b"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_OSS_120B_EXACTO"] = "openai/gpt-oss-120b:exacto"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_OSS_20B_FREE"] = "openai/gpt-oss-20b:free"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_OSS_20B"] = "openai/gpt-oss-20b"; E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_OPUS_4_1"] = "anthropic/claude-opus-4.1"; @@ -257272,6 +257384,7 @@ var E_OPENROUTER_MODEL; E_OPENROUTER_MODEL["MODEL_Z_AI_GLM_4_32B"] = "z-ai/glm-4-32b"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_CODER_FREE"] = "qwen/qwen3-coder:free"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_CODER"] = "qwen/qwen3-coder"; + E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_CODER_EXACTO"] = "qwen/qwen3-coder:exacto"; E_OPENROUTER_MODEL["MODEL_BYTEDANCE_UI_TARS_1_5_7B"] = "bytedance/ui-tars-1.5-7b"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_2_5_FLASH_LITE"] = "google/gemini-2.5-flash-lite"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_235B_A22B_2507"] = "qwen/qwen3-235b-a22b-2507"; @@ -257284,42 +257397,32 @@ var E_OPENROUTER_MODEL; E_OPENROUTER_MODEL["MODEL_COGNITIVECOMPUTATIONS_DOLPHIN_MISTRAL_24B_VENICE_EDITION_FREE"] = "cognitivecomputations/dolphin-mistral-24b-venice-edition:free"; E_OPENROUTER_MODEL["MODEL_X_AI_GROK_4"] = "x-ai/grok-4"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMMA_3N_E2B_IT_FREE"] = "google/gemma-3n-e2b-it:free"; - E_OPENROUTER_MODEL["MODEL_TENCENT_HUNYUAN_A13B_INSTRUCT_FREE"] = "tencent/hunyuan-a13b-instruct:free"; E_OPENROUTER_MODEL["MODEL_TENCENT_HUNYUAN_A13B_INSTRUCT"] = "tencent/hunyuan-a13b-instruct"; E_OPENROUTER_MODEL["MODEL_TNGTECH_DEEPSEEK_R1T2_CHIMERA_FREE"] = "tngtech/deepseek-r1t2-chimera:free"; + E_OPENROUTER_MODEL["MODEL_TNGTECH_DEEPSEEK_R1T2_CHIMERA"] = "tngtech/deepseek-r1t2-chimera"; E_OPENROUTER_MODEL["MODEL_MORPH_MORPH_V3_LARGE"] = "morph/morph-v3-large"; E_OPENROUTER_MODEL["MODEL_MORPH_MORPH_V3_FAST"] = "morph/morph-v3-fast"; E_OPENROUTER_MODEL["MODEL_BAIDU_ERNIE_4_5_VL_424B_A47B"] = "baidu/ernie-4.5-vl-424b-a47b"; E_OPENROUTER_MODEL["MODEL_BAIDU_ERNIE_4_5_300B_A47B"] = "baidu/ernie-4.5-300b-a47b"; - E_OPENROUTER_MODEL["MODEL_THEDRUMMER_ANUBIS_70B_V1_1"] = "thedrummer/anubis-70b-v1.1"; E_OPENROUTER_MODEL["MODEL_INCEPTION_MERCURY"] = "inception/mercury"; - E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_SMALL_3_2_24B_INSTRUCT_FREE"] = "mistralai/mistral-small-3.2-24b-instruct:free"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_SMALL_3_2_24B_INSTRUCT"] = "mistralai/mistral-small-3.2-24b-instruct"; E_OPENROUTER_MODEL["MODEL_MINIMAX_MINIMAX_M1"] = "minimax/minimax-m1"; - E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_2_5_FLASH_LITE_PREVIEW_06_17"] = "google/gemini-2.5-flash-lite-preview-06-17"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_2_5_FLASH"] = "google/gemini-2.5-flash"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_2_5_PRO"] = "google/gemini-2.5-pro"; - E_OPENROUTER_MODEL["MODEL_MOONSHOTAI_KIMI_DEV_72B_FREE"] = "moonshotai/kimi-dev-72b:free"; E_OPENROUTER_MODEL["MODEL_MOONSHOTAI_KIMI_DEV_72B"] = "moonshotai/kimi-dev-72b"; E_OPENROUTER_MODEL["MODEL_OPENAI_O3_PRO"] = "openai/o3-pro"; E_OPENROUTER_MODEL["MODEL_X_AI_GROK_3_MINI"] = "x-ai/grok-3-mini"; E_OPENROUTER_MODEL["MODEL_X_AI_GROK_3"] = "x-ai/grok-3"; - E_OPENROUTER_MODEL["MODEL_MISTRALAI_MAGISTRAL_SMALL_2506"] = "mistralai/magistral-small-2506"; - E_OPENROUTER_MODEL["MODEL_MISTRALAI_MAGISTRAL_MEDIUM_2506"] = "mistralai/magistral-medium-2506"; - E_OPENROUTER_MODEL["MODEL_MISTRALAI_MAGISTRAL_MEDIUM_2506_THINKING"] = "mistralai/magistral-medium-2506:thinking"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_2_5_PRO_PREVIEW"] = "google/gemini-2.5-pro-preview"; - E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_R1_0528_QWEN3_8B_FREE"] = "deepseek/deepseek-r1-0528-qwen3-8b:free"; E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_R1_0528_QWEN3_8B"] = "deepseek/deepseek-r1-0528-qwen3-8b"; E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_R1_0528_FREE"] = "deepseek/deepseek-r1-0528:free"; E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_R1_0528"] = "deepseek/deepseek-r1-0528"; E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_OPUS_4"] = "anthropic/claude-opus-4"; E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_SONNET_4"] = "anthropic/claude-sonnet-4"; - E_OPENROUTER_MODEL["MODEL_MISTRALAI_DEVSTRAL_SMALL_2505_FREE"] = "mistralai/devstral-small-2505:free"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_DEVSTRAL_SMALL_2505"] = "mistralai/devstral-small-2505"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMMA_3N_E4B_IT_FREE"] = "google/gemma-3n-e4b-it:free"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMMA_3N_E4B_IT"] = "google/gemma-3n-e4b-it"; E_OPENROUTER_MODEL["MODEL_OPENAI_CODEX_MINI"] = "openai/codex-mini"; - E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_3_8B_INSTRUCT_FREE"] = "meta-llama/llama-3.3-8b-instruct:free"; E_OPENROUTER_MODEL["MODEL_NOUSRESEARCH_DEEPHERMES_3_MISTRAL_24B_PREVIEW"] = "nousresearch/deephermes-3-mistral-24b-preview"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_MEDIUM_3"] = "mistralai/mistral-medium-3"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_2_5_PRO_PREVIEW_05_06"] = "google/gemini-2.5-pro-preview-05-06"; @@ -257332,47 +257435,29 @@ var E_OPENROUTER_MODEL; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_4B_FREE"] = "qwen/qwen3-4b:free"; E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_PROVER_V2"] = "deepseek/deepseek-prover-v2"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_GUARD_4_12B"] = "meta-llama/llama-guard-4-12b"; - E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_30B_A3B_FREE"] = "qwen/qwen3-30b-a3b:free"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_30B_A3B"] = "qwen/qwen3-30b-a3b"; - E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_8B_FREE"] = "qwen/qwen3-8b:free"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_8B"] = "qwen/qwen3-8b"; - E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_14B_FREE"] = "qwen/qwen3-14b:free"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_14B"] = "qwen/qwen3-14b"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_32B"] = "qwen/qwen3-32b"; - E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_235B_A22B_FREE"] = "qwen/qwen3-235b-a22b:free"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN3_235B_A22B"] = "qwen/qwen3-235b-a22b"; E_OPENROUTER_MODEL["MODEL_TNGTECH_DEEPSEEK_R1T_CHIMERA_FREE"] = "tngtech/deepseek-r1t-chimera:free"; E_OPENROUTER_MODEL["MODEL_TNGTECH_DEEPSEEK_R1T_CHIMERA"] = "tngtech/deepseek-r1t-chimera"; - E_OPENROUTER_MODEL["MODEL_MICROSOFT_MAI_DS_R1_FREE"] = "microsoft/mai-ds-r1:free"; - E_OPENROUTER_MODEL["MODEL_MICROSOFT_MAI_DS_R1"] = "microsoft/mai-ds-r1"; - E_OPENROUTER_MODEL["MODEL_THUDM_GLM_Z1_32B"] = "thudm/glm-z1-32b"; E_OPENROUTER_MODEL["MODEL_OPENAI_O4_MINI_HIGH"] = "openai/o4-mini-high"; E_OPENROUTER_MODEL["MODEL_OPENAI_O3"] = "openai/o3"; E_OPENROUTER_MODEL["MODEL_OPENAI_O4_MINI"] = "openai/o4-mini"; - E_OPENROUTER_MODEL["MODEL_SHISA_AI_SHISA_V2_LLAMA3_3_70B_FREE"] = "shisa-ai/shisa-v2-llama3.3-70b:free"; - E_OPENROUTER_MODEL["MODEL_SHISA_AI_SHISA_V2_LLAMA3_3_70B"] = "shisa-ai/shisa-v2-llama3.3-70b"; + E_OPENROUTER_MODEL["MODEL_QWEN_QWEN2_5_CODER_7B_INSTRUCT"] = "qwen/qwen2.5-coder-7b-instruct"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4_1"] = "openai/gpt-4.1"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4_1_MINI"] = "openai/gpt-4.1-mini"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4_1_NANO"] = "openai/gpt-4.1-nano"; E_OPENROUTER_MODEL["MODEL_ELEUTHERAI_LLEMMA_7B"] = "eleutherai/llemma_7b"; E_OPENROUTER_MODEL["MODEL_ALFREDPROS_CODELLAMA_7B_INSTRUCT_SOLIDITY"] = "alfredpros/codellama-7b-instruct-solidity"; - E_OPENROUTER_MODEL["MODEL_ARLIAI_QWQ_32B_ARLIAI_RPR_V1_FREE"] = "arliai/qwq-32b-arliai-rpr-v1:free"; E_OPENROUTER_MODEL["MODEL_ARLIAI_QWQ_32B_ARLIAI_RPR_V1"] = "arliai/qwq-32b-arliai-rpr-v1"; - E_OPENROUTER_MODEL["MODEL_AGENTICA_ORG_DEEPCODER_14B_PREVIEW_FREE"] = "agentica-org/deepcoder-14b-preview:free"; - E_OPENROUTER_MODEL["MODEL_AGENTICA_ORG_DEEPCODER_14B_PREVIEW"] = "agentica-org/deepcoder-14b-preview"; - E_OPENROUTER_MODEL["MODEL_MOONSHOTAI_KIMI_VL_A3B_THINKING_FREE"] = "moonshotai/kimi-vl-a3b-thinking:free"; - E_OPENROUTER_MODEL["MODEL_MOONSHOTAI_KIMI_VL_A3B_THINKING"] = "moonshotai/kimi-vl-a3b-thinking"; E_OPENROUTER_MODEL["MODEL_X_AI_GROK_3_MINI_BETA"] = "x-ai/grok-3-mini-beta"; E_OPENROUTER_MODEL["MODEL_X_AI_GROK_3_BETA"] = "x-ai/grok-3-beta"; E_OPENROUTER_MODEL["MODEL_NVIDIA_LLAMA_3_1_NEMOTRON_ULTRA_253B_V1"] = "nvidia/llama-3.1-nemotron-ultra-253b-v1"; - E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_4_MAVERICK_FREE"] = "meta-llama/llama-4-maverick:free"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_4_MAVERICK"] = "meta-llama/llama-4-maverick"; - E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_4_SCOUT_FREE"] = "meta-llama/llama-4-scout:free"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_4_SCOUT"] = "meta-llama/llama-4-scout"; - E_OPENROUTER_MODEL["MODEL_ALLENAI_MOLMO_7B_D"] = "allenai/molmo-7b-d"; - E_OPENROUTER_MODEL["MODEL_QWEN_QWEN2_5_VL_32B_INSTRUCT_FREE"] = "qwen/qwen2.5-vl-32b-instruct:free"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN2_5_VL_32B_INSTRUCT"] = "qwen/qwen2.5-vl-32b-instruct"; - E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_CHAT_V3_0324_FREE"] = "deepseek/deepseek-chat-v3-0324:free"; E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_CHAT_V3_0324"] = "deepseek/deepseek-chat-v3-0324"; E_OPENROUTER_MODEL["MODEL_OPENAI_O1_PRO"] = "openai/o1-pro"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_SMALL_3_1_24B_INSTRUCT_FREE"] = "mistralai/mistral-small-3.1-24b-instruct:free"; @@ -257387,27 +257472,18 @@ var E_OPENROUTER_MODEL; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4O_SEARCH_PREVIEW"] = "openai/gpt-4o-search-preview"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMMA_3_27B_IT_FREE"] = "google/gemma-3-27b-it:free"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMMA_3_27B_IT"] = "google/gemma-3-27b-it"; - E_OPENROUTER_MODEL["MODEL_THEDRUMMER_ANUBIS_PRO_105B_V1"] = "thedrummer/anubis-pro-105b-v1"; E_OPENROUTER_MODEL["MODEL_THEDRUMMER_SKYFALL_36B_V2"] = "thedrummer/skyfall-36b-v2"; E_OPENROUTER_MODEL["MODEL_MICROSOFT_PHI_4_MULTIMODAL_INSTRUCT"] = "microsoft/phi-4-multimodal-instruct"; E_OPENROUTER_MODEL["MODEL_PERPLEXITY_SONAR_REASONING_PRO"] = "perplexity/sonar-reasoning-pro"; E_OPENROUTER_MODEL["MODEL_PERPLEXITY_SONAR_PRO"] = "perplexity/sonar-pro"; E_OPENROUTER_MODEL["MODEL_PERPLEXITY_SONAR_DEEP_RESEARCH"] = "perplexity/sonar-deep-research"; - E_OPENROUTER_MODEL["MODEL_QWEN_QWQ_32B_FREE"] = "qwen/qwq-32b:free"; E_OPENROUTER_MODEL["MODEL_QWEN_QWQ_32B"] = "qwen/qwq-32b"; - E_OPENROUTER_MODEL["MODEL_NOUSRESEARCH_DEEPHERMES_3_LLAMA_3_8B_PREVIEW_FREE"] = "nousresearch/deephermes-3-llama-3-8b-preview:free"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_2_0_FLASH_LITE_001"] = "google/gemini-2.0-flash-lite-001"; - E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_3_7_SONNET"] = "anthropic/claude-3.7-sonnet"; E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_3_7_SONNET_THINKING"] = "anthropic/claude-3.7-sonnet:thinking"; - E_OPENROUTER_MODEL["MODEL_PERPLEXITY_R1_1776"] = "perplexity/r1-1776"; + E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_3_7_SONNET"] = "anthropic/claude-3.7-sonnet"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_SABA"] = "mistralai/mistral-saba"; - E_OPENROUTER_MODEL["MODEL_COGNITIVECOMPUTATIONS_DOLPHIN3_0_R1_MISTRAL_24B_FREE"] = "cognitivecomputations/dolphin3.0-r1-mistral-24b:free"; - E_OPENROUTER_MODEL["MODEL_COGNITIVECOMPUTATIONS_DOLPHIN3_0_R1_MISTRAL_24B"] = "cognitivecomputations/dolphin3.0-r1-mistral-24b"; - E_OPENROUTER_MODEL["MODEL_COGNITIVECOMPUTATIONS_DOLPHIN3_0_MISTRAL_24B_FREE"] = "cognitivecomputations/dolphin3.0-mistral-24b:free"; - E_OPENROUTER_MODEL["MODEL_COGNITIVECOMPUTATIONS_DOLPHIN3_0_MISTRAL_24B"] = "cognitivecomputations/dolphin3.0-mistral-24b"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_GUARD_3_8B"] = "meta-llama/llama-guard-3-8b"; E_OPENROUTER_MODEL["MODEL_OPENAI_O3_MINI_HIGH"] = "openai/o3-mini-high"; - E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_R1_DISTILL_LLAMA_8B"] = "deepseek/deepseek-r1-distill-llama-8b"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_2_0_FLASH_001"] = "google/gemini-2.0-flash-001"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN_VL_PLUS"] = "qwen/qwen-vl-plus"; E_OPENROUTER_MODEL["MODEL_AION_LABS_AION_1_0"] = "aion-labs/aion-1.0"; @@ -257415,26 +257491,20 @@ var E_OPENROUTER_MODEL; E_OPENROUTER_MODEL["MODEL_AION_LABS_AION_RP_LLAMA_3_1_8B"] = "aion-labs/aion-rp-llama-3.1-8b"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN_VL_MAX"] = "qwen/qwen-vl-max"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN_TURBO"] = "qwen/qwen-turbo"; - E_OPENROUTER_MODEL["MODEL_QWEN_QWEN2_5_VL_72B_INSTRUCT_FREE"] = "qwen/qwen2.5-vl-72b-instruct:free"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN2_5_VL_72B_INSTRUCT"] = "qwen/qwen2.5-vl-72b-instruct"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN_PLUS"] = "qwen/qwen-plus"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN_MAX"] = "qwen/qwen-max"; E_OPENROUTER_MODEL["MODEL_OPENAI_O3_MINI"] = "openai/o3-mini"; - E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_SMALL_24B_INSTRUCT_2501_FREE"] = "mistralai/mistral-small-24b-instruct-2501:free"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_SMALL_24B_INSTRUCT_2501"] = "mistralai/mistral-small-24b-instruct-2501"; E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_R1_DISTILL_QWEN_32B"] = "deepseek/deepseek-r1-distill-qwen-32b"; E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_R1_DISTILL_QWEN_14B"] = "deepseek/deepseek-r1-distill-qwen-14b"; E_OPENROUTER_MODEL["MODEL_PERPLEXITY_SONAR_REASONING"] = "perplexity/sonar-reasoning"; E_OPENROUTER_MODEL["MODEL_PERPLEXITY_SONAR"] = "perplexity/sonar"; - E_OPENROUTER_MODEL["MODEL_LIQUID_LFM_7B"] = "liquid/lfm-7b"; - E_OPENROUTER_MODEL["MODEL_LIQUID_LFM_3B"] = "liquid/lfm-3b"; - E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_R1_DISTILL_LLAMA_70B_FREE"] = "deepseek/deepseek-r1-distill-llama-70b:free"; E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_R1_DISTILL_LLAMA_70B"] = "deepseek/deepseek-r1-distill-llama-70b"; - E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_R1_FREE"] = "deepseek/deepseek-r1:free"; E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_R1"] = "deepseek/deepseek-r1"; E_OPENROUTER_MODEL["MODEL_MINIMAX_MINIMAX_01"] = "minimax/minimax-01"; - E_OPENROUTER_MODEL["MODEL_MISTRALAI_CODESTRAL_2501"] = "mistralai/codestral-2501"; E_OPENROUTER_MODEL["MODEL_MICROSOFT_PHI_4"] = "microsoft/phi-4"; + E_OPENROUTER_MODEL["MODEL_SAO10K_L3_1_70B_HANAMI_X1"] = "sao10k/l3.1-70b-hanami-x1"; E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_CHAT"] = "deepseek/deepseek-chat"; E_OPENROUTER_MODEL["MODEL_SAO10K_L3_3_EURYALE_70B"] = "sao10k/l3.3-euryale-70b"; E_OPENROUTER_MODEL["MODEL_OPENAI_O1"] = "openai/o1"; @@ -257445,45 +257515,40 @@ var E_OPENROUTER_MODEL; E_OPENROUTER_MODEL["MODEL_AMAZON_NOVA_LITE_V1"] = "amazon/nova-lite-v1"; E_OPENROUTER_MODEL["MODEL_AMAZON_NOVA_MICRO_V1"] = "amazon/nova-micro-v1"; E_OPENROUTER_MODEL["MODEL_AMAZON_NOVA_PRO_V1"] = "amazon/nova-pro-v1"; - E_OPENROUTER_MODEL["MODEL_QWEN_QWQ_32B_PREVIEW"] = "qwen/qwq-32b-preview"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4O_2024_11_20"] = "openai/gpt-4o-2024-11-20"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_LARGE_2411"] = "mistralai/mistral-large-2411"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_LARGE_2407"] = "mistralai/mistral-large-2407"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_PIXTRAL_LARGE_2411"] = "mistralai/pixtral-large-2411"; - E_OPENROUTER_MODEL["MODEL_QWEN_QWEN_2_5_CODER_32B_INSTRUCT_FREE"] = "qwen/qwen-2.5-coder-32b-instruct:free"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN_2_5_CODER_32B_INSTRUCT"] = "qwen/qwen-2.5-coder-32b-instruct"; E_OPENROUTER_MODEL["MODEL_RAIFLE_SORCERERLM_8X22B"] = "raifle/sorcererlm-8x22b"; E_OPENROUTER_MODEL["MODEL_THEDRUMMER_UNSLOPNEMO_12B"] = "thedrummer/unslopnemo-12b"; - E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_3_5_HAIKU"] = "anthropic/claude-3.5-haiku"; E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_3_5_HAIKU_20241022"] = "anthropic/claude-3.5-haiku-20241022"; + E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_3_5_HAIKU"] = "anthropic/claude-3.5-haiku"; E_OPENROUTER_MODEL["MODEL_ANTHRACITE_ORG_MAGNUM_V4_72B"] = "anthracite-org/magnum-v4-72b"; E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_3_5_SONNET"] = "anthropic/claude-3.5-sonnet"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MINISTRAL_8B"] = "mistralai/ministral-8b"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MINISTRAL_3B"] = "mistralai/ministral-3b"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN_2_5_7B_INSTRUCT"] = "qwen/qwen-2.5-7b-instruct"; E_OPENROUTER_MODEL["MODEL_NVIDIA_LLAMA_3_1_NEMOTRON_70B_INSTRUCT"] = "nvidia/llama-3.1-nemotron-70b-instruct"; - E_OPENROUTER_MODEL["MODEL_INFLECTION_INFLECTION_3_PRODUCTIVITY"] = "inflection/inflection-3-productivity"; E_OPENROUTER_MODEL["MODEL_INFLECTION_INFLECTION_3_PI"] = "inflection/inflection-3-pi"; - E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_FLASH_1_5_8B"] = "google/gemini-flash-1.5-8b"; + E_OPENROUTER_MODEL["MODEL_INFLECTION_INFLECTION_3_PRODUCTIVITY"] = "inflection/inflection-3-productivity"; E_OPENROUTER_MODEL["MODEL_THEDRUMMER_ROCINANTE_12B"] = "thedrummer/rocinante-12b"; - E_OPENROUTER_MODEL["MODEL_ANTHRACITE_ORG_MAGNUM_V2_72B"] = "anthracite-org/magnum-v2-72b"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_2_3B_INSTRUCT_FREE"] = "meta-llama/llama-3.2-3b-instruct:free"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_2_3B_INSTRUCT"] = "meta-llama/llama-3.2-3b-instruct"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_2_1B_INSTRUCT"] = "meta-llama/llama-3.2-1b-instruct"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_2_90B_VISION_INSTRUCT"] = "meta-llama/llama-3.2-90b-vision-instruct"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_2_11B_VISION_INSTRUCT"] = "meta-llama/llama-3.2-11b-vision-instruct"; - E_OPENROUTER_MODEL["MODEL_QWEN_QWEN_2_5_72B_INSTRUCT_FREE"] = "qwen/qwen-2.5-72b-instruct:free"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN_2_5_72B_INSTRUCT"] = "qwen/qwen-2.5-72b-instruct"; E_OPENROUTER_MODEL["MODEL_NEVERSLEEP_LLAMA_3_1_LUMIMAID_8B"] = "neversleep/llama-3.1-lumimaid-8b"; - E_OPENROUTER_MODEL["MODEL_OPENAI_O1_MINI"] = "openai/o1-mini"; - E_OPENROUTER_MODEL["MODEL_OPENAI_O1_MINI_2024_09_12"] = "openai/o1-mini-2024-09-12"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_PIXTRAL_12B"] = "mistralai/pixtral-12b"; - E_OPENROUTER_MODEL["MODEL_COHERE_COMMAND_R_PLUS_08_2024"] = "cohere/command-r-plus-08-2024"; E_OPENROUTER_MODEL["MODEL_COHERE_COMMAND_R_08_2024"] = "cohere/command-r-08-2024"; - E_OPENROUTER_MODEL["MODEL_QWEN_QWEN_2_5_VL_7B_INSTRUCT"] = "qwen/qwen-2.5-vl-7b-instruct"; + E_OPENROUTER_MODEL["MODEL_COHERE_COMMAND_R_PLUS_08_2024"] = "cohere/command-r-plus-08-2024"; E_OPENROUTER_MODEL["MODEL_SAO10K_L3_1_EURYALE_70B"] = "sao10k/l3.1-euryale-70b"; + E_OPENROUTER_MODEL["MODEL_QWEN_QWEN_2_5_VL_7B_INSTRUCT_FREE"] = "qwen/qwen-2.5-vl-7b-instruct:free"; + E_OPENROUTER_MODEL["MODEL_QWEN_QWEN_2_5_VL_7B_INSTRUCT"] = "qwen/qwen-2.5-vl-7b-instruct"; E_OPENROUTER_MODEL["MODEL_MICROSOFT_PHI_3_5_MINI_128K_INSTRUCT"] = "microsoft/phi-3.5-mini-128k-instruct"; E_OPENROUTER_MODEL["MODEL_NOUSRESEARCH_HERMES_3_LLAMA_3_1_70B"] = "nousresearch/hermes-3-llama-3.1-70b"; + E_OPENROUTER_MODEL["MODEL_NOUSRESEARCH_HERMES_3_LLAMA_3_1_405B_FREE"] = "nousresearch/hermes-3-llama-3.1-405b:free"; E_OPENROUTER_MODEL["MODEL_NOUSRESEARCH_HERMES_3_LLAMA_3_1_405B"] = "nousresearch/hermes-3-llama-3.1-405b"; E_OPENROUTER_MODEL["MODEL_OPENAI_CHATGPT_4O_LATEST"] = "openai/chatgpt-4o-latest"; E_OPENROUTER_MODEL["MODEL_SAO10K_L3_LUNARIS_8B"] = "sao10k/l3-lunaris-8b"; @@ -257493,14 +257558,11 @@ var E_OPENROUTER_MODEL; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_1_405B_INSTRUCT_FREE"] = "meta-llama/llama-3.1-405b-instruct:free"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_1_405B_INSTRUCT"] = "meta-llama/llama-3.1-405b-instruct"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_1_70B_INSTRUCT"] = "meta-llama/llama-3.1-70b-instruct"; - E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_NEMO_FREE"] = "mistralai/mistral-nemo:free"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_NEMO"] = "mistralai/mistral-nemo"; - E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4O_MINI"] = "openai/gpt-4o-mini"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4O_MINI_2024_07_18"] = "openai/gpt-4o-mini-2024-07-18"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4O_MINI"] = "openai/gpt-4o-mini"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMMA_2_27B_IT"] = "google/gemma-2-27b-it"; - E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMMA_2_9B_IT_FREE"] = "google/gemma-2-9b-it:free"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMMA_2_9B_IT"] = "google/gemma-2-9b-it"; - E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_3_5_SONNET_20240620"] = "anthropic/claude-3.5-sonnet-20240620"; E_OPENROUTER_MODEL["MODEL_SAO10K_L3_EURYALE_70B"] = "sao10k/l3-euryale-70b"; E_OPENROUTER_MODEL["MODEL_NOUSRESEARCH_HERMES_2_PRO_LLAMA_3_8B"] = "nousresearch/hermes-2-pro-llama-3-8b"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_7B_INSTRUCT_FREE"] = "mistralai/mistral-7b-instruct:free"; @@ -257508,30 +257570,22 @@ var E_OPENROUTER_MODEL; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_7B_INSTRUCT_V0_3"] = "mistralai/mistral-7b-instruct-v0.3"; E_OPENROUTER_MODEL["MODEL_MICROSOFT_PHI_3_MINI_128K_INSTRUCT"] = "microsoft/phi-3-mini-128k-instruct"; E_OPENROUTER_MODEL["MODEL_MICROSOFT_PHI_3_MEDIUM_128K_INSTRUCT"] = "microsoft/phi-3-medium-128k-instruct"; - E_OPENROUTER_MODEL["MODEL_NEVERSLEEP_LLAMA_3_LUMIMAID_70B"] = "neversleep/llama-3-lumimaid-70b"; - E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_FLASH_1_5"] = "google/gemini-flash-1.5"; - E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4O"] = "openai/gpt-4o"; - E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4O_EXTENDED"] = "openai/gpt-4o:extended"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_GUARD_2_8B"] = "meta-llama/llama-guard-2-8b"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4O_2024_05_13"] = "openai/gpt-4o-2024-05-13"; - E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_8B_INSTRUCT"] = "meta-llama/llama-3-8b-instruct"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4O"] = "openai/gpt-4o"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4O_EXTENDED"] = "openai/gpt-4o:extended"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_70B_INSTRUCT"] = "meta-llama/llama-3-70b-instruct"; + E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_8B_INSTRUCT"] = "meta-llama/llama-3-8b-instruct"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MIXTRAL_8X22B_INSTRUCT"] = "mistralai/mixtral-8x22b-instruct"; E_OPENROUTER_MODEL["MODEL_MICROSOFT_WIZARDLM_2_8X22B"] = "microsoft/wizardlm-2-8x22b"; - E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_PRO_1_5"] = "google/gemini-pro-1.5"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4_TURBO"] = "openai/gpt-4-turbo"; - E_OPENROUTER_MODEL["MODEL_COHERE_COMMAND_R_PLUS"] = "cohere/command-r-plus"; - E_OPENROUTER_MODEL["MODEL_COHERE_COMMAND_R_PLUS_04_2024"] = "cohere/command-r-plus-04-2024"; - E_OPENROUTER_MODEL["MODEL_COHERE_COMMAND"] = "cohere/command"; - E_OPENROUTER_MODEL["MODEL_COHERE_COMMAND_R"] = "cohere/command-r"; E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_3_HAIKU"] = "anthropic/claude-3-haiku"; E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_3_OPUS"] = "anthropic/claude-3-opus"; - E_OPENROUTER_MODEL["MODEL_COHERE_COMMAND_R_03_2024"] = "cohere/command-r-03-2024"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_LARGE"] = "mistralai/mistral-large"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_3_5_TURBO_0613"] = "openai/gpt-3.5-turbo-0613"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4_TURBO_PREVIEW"] = "openai/gpt-4-turbo-preview"; - E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_SMALL"] = "mistralai/mistral-small"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_TINY"] = "mistralai/mistral-tiny"; + E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_7B_INSTRUCT_V0_2"] = "mistralai/mistral-7b-instruct-v0.2"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MIXTRAL_8X7B_INSTRUCT"] = "mistralai/mixtral-8x7b-instruct"; E_OPENROUTER_MODEL["MODEL_NEVERSLEEP_NOROMAID_20B"] = "neversleep/noromaid-20b"; E_OPENROUTER_MODEL["MODEL_ALPINDALE_GOLIATH_120B"] = "alpindale/goliath-120b"; @@ -257543,17 +257597,26 @@ var E_OPENROUTER_MODEL; E_OPENROUTER_MODEL["MODEL_MANCER_WEAVER"] = "mancer/weaver"; E_OPENROUTER_MODEL["MODEL_UNDI95_REMM_SLERP_L2_13B"] = "undi95/remm-slerp-l2-13b"; E_OPENROUTER_MODEL["MODEL_GRYPHE_MYTHOMAX_L2_13B"] = "gryphe/mythomax-l2-13b"; - E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_3_5_TURBO"] = "openai/gpt-3.5-turbo"; - E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4"] = "openai/gpt-4"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4_0314"] = "openai/gpt-4-0314"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4"] = "openai/gpt-4"; + E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_3_5_TURBO"] = "openai/gpt-3.5-turbo"; })(E_OPENROUTER_MODEL || (E_OPENROUTER_MODEL = {})); -//# 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+//# 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;// ./dist-in/models/cache/openrouter-models-free.js var E_OPENROUTER_MODEL_FREE; (function (E_OPENROUTER_MODEL_FREE) { - E_OPENROUTER_MODEL_FREE["MODEL_FREE_X_AI_GROK_4_FAST_FREE"] = "x-ai/grok-4-fast:free"; + E_OPENROUTER_MODEL_FREE["MODEL_FREE_ALLENAI_OLMO_3_1_32B_THINK_FREE"] = "allenai/olmo-3.1-32b-think:free"; + E_OPENROUTER_MODEL_FREE["MODEL_FREE_XIAOMI_MIMO_V2_FLASH_FREE"] = "xiaomi/mimo-v2-flash:free"; + E_OPENROUTER_MODEL_FREE["MODEL_FREE_NVIDIA_NEMOTRON_3_NANO_30B_A3B_FREE"] = "nvidia/nemotron-3-nano-30b-a3b:free"; + E_OPENROUTER_MODEL_FREE["MODEL_FREE_MISTRALAI_DEVSTRAL_2512_FREE"] = "mistralai/devstral-2512:free"; + E_OPENROUTER_MODEL_FREE["MODEL_FREE_NEX_AGI_DEEPSEEK_V3_1_NEX_N1_FREE"] = "nex-agi/deepseek-v3.1-nex-n1:free"; + E_OPENROUTER_MODEL_FREE["MODEL_FREE_ARCEE_AI_TRINITY_MINI_FREE"] = "arcee-ai/trinity-mini:free"; + E_OPENROUTER_MODEL_FREE["MODEL_FREE_TNGTECH_TNG_R1T_CHIMERA_FREE"] = "tngtech/tng-r1t-chimera:free"; + E_OPENROUTER_MODEL_FREE["MODEL_FREE_ALLENAI_OLMO_3_32B_THINK_FREE"] = "allenai/olmo-3-32b-think:free"; + E_OPENROUTER_MODEL_FREE["MODEL_FREE_KWAIPILOT_KAT_CODER_PRO_FREE"] = "kwaipilot/kat-coder-pro:free"; + E_OPENROUTER_MODEL_FREE["MODEL_FREE_NVIDIA_NEMOTRON_NANO_12B_V2_VL_FREE"] = "nvidia/nemotron-nano-12b-v2-vl:free"; + E_OPENROUTER_MODEL_FREE["MODEL_FREE_ALIBABA_TONGYI_DEEPRESEARCH_30B_A3B_FREE"] = "alibaba/tongyi-deepresearch-30b-a3b:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_NVIDIA_NEMOTRON_NANO_9B_V2_FREE"] = "nvidia/nemotron-nano-9b-v2:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_DEEPSEEK_DEEPSEEK_CHAT_V3_1_FREE"] = "deepseek/deepseek-chat-v3.1:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_OPENAI_GPT_OSS_120B_FREE"] = "openai/gpt-oss-120b:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_OPENAI_GPT_OSS_20B_FREE"] = "openai/gpt-oss-20b:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_Z_AI_GLM_4_5_AIR_FREE"] = "z-ai/glm-4.5-air:free"; @@ -257561,53 +257624,24 @@ var E_OPENROUTER_MODEL_FREE; E_OPENROUTER_MODEL_FREE["MODEL_FREE_MOONSHOTAI_KIMI_K2_FREE"] = "moonshotai/kimi-k2:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_COGNITIVECOMPUTATIONS_DOLPHIN_MISTRAL_24B_VENICE_EDITION_FREE"] = "cognitivecomputations/dolphin-mistral-24b-venice-edition:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_GOOGLE_GEMMA_3N_E2B_IT_FREE"] = "google/gemma-3n-e2b-it:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_TENCENT_HUNYUAN_A13B_INSTRUCT_FREE"] = "tencent/hunyuan-a13b-instruct:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_TNGTECH_DEEPSEEK_R1T2_CHIMERA_FREE"] = "tngtech/deepseek-r1t2-chimera:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_MISTRALAI_MISTRAL_SMALL_3_2_24B_INSTRUCT_FREE"] = "mistralai/mistral-small-3.2-24b-instruct:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_MOONSHOTAI_KIMI_DEV_72B_FREE"] = "moonshotai/kimi-dev-72b:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_DEEPSEEK_DEEPSEEK_R1_0528_QWEN3_8B_FREE"] = "deepseek/deepseek-r1-0528-qwen3-8b:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_DEEPSEEK_DEEPSEEK_R1_0528_FREE"] = "deepseek/deepseek-r1-0528:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_MISTRALAI_DEVSTRAL_SMALL_2505_FREE"] = "mistralai/devstral-small-2505:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_GOOGLE_GEMMA_3N_E4B_IT_FREE"] = "google/gemma-3n-e4b-it:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_META_LLAMA_LLAMA_3_3_8B_INSTRUCT_FREE"] = "meta-llama/llama-3.3-8b-instruct:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_QWEN_QWEN3_4B_FREE"] = "qwen/qwen3-4b:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_QWEN_QWEN3_30B_A3B_FREE"] = "qwen/qwen3-30b-a3b:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_QWEN_QWEN3_8B_FREE"] = "qwen/qwen3-8b:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_QWEN_QWEN3_14B_FREE"] = "qwen/qwen3-14b:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_QWEN_QWEN3_235B_A22B_FREE"] = "qwen/qwen3-235b-a22b:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_TNGTECH_DEEPSEEK_R1T_CHIMERA_FREE"] = "tngtech/deepseek-r1t-chimera:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_MICROSOFT_MAI_DS_R1_FREE"] = "microsoft/mai-ds-r1:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_SHISA_AI_SHISA_V2_LLAMA3_3_70B_FREE"] = "shisa-ai/shisa-v2-llama3.3-70b:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_ARLIAI_QWQ_32B_ARLIAI_RPR_V1_FREE"] = "arliai/qwq-32b-arliai-rpr-v1:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_AGENTICA_ORG_DEEPCODER_14B_PREVIEW_FREE"] = "agentica-org/deepcoder-14b-preview:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_MOONSHOTAI_KIMI_VL_A3B_THINKING_FREE"] = "moonshotai/kimi-vl-a3b-thinking:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_META_LLAMA_LLAMA_4_MAVERICK_FREE"] = "meta-llama/llama-4-maverick:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_META_LLAMA_LLAMA_4_SCOUT_FREE"] = "meta-llama/llama-4-scout:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_QWEN_QWEN2_5_VL_32B_INSTRUCT_FREE"] = "qwen/qwen2.5-vl-32b-instruct:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_DEEPSEEK_DEEPSEEK_CHAT_V3_0324_FREE"] = "deepseek/deepseek-chat-v3-0324:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_MISTRALAI_MISTRAL_SMALL_3_1_24B_INSTRUCT_FREE"] = "mistralai/mistral-small-3.1-24b-instruct:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_GOOGLE_GEMMA_3_4B_IT_FREE"] = "google/gemma-3-4b-it:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_GOOGLE_GEMMA_3_12B_IT_FREE"] = "google/gemma-3-12b-it:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_GOOGLE_GEMMA_3_27B_IT_FREE"] = "google/gemma-3-27b-it:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_QWEN_QWQ_32B_FREE"] = "qwen/qwq-32b:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_NOUSRESEARCH_DEEPHERMES_3_LLAMA_3_8B_PREVIEW_FREE"] = "nousresearch/deephermes-3-llama-3-8b-preview:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_COGNITIVECOMPUTATIONS_DOLPHIN3_0_R1_MISTRAL_24B_FREE"] = "cognitivecomputations/dolphin3.0-r1-mistral-24b:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_COGNITIVECOMPUTATIONS_DOLPHIN3_0_MISTRAL_24B_FREE"] = "cognitivecomputations/dolphin3.0-mistral-24b:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_QWEN_QWEN2_5_VL_72B_INSTRUCT_FREE"] = "qwen/qwen2.5-vl-72b-instruct:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_MISTRALAI_MISTRAL_SMALL_24B_INSTRUCT_2501_FREE"] = "mistralai/mistral-small-24b-instruct-2501:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_DEEPSEEK_DEEPSEEK_R1_DISTILL_LLAMA_70B_FREE"] = "deepseek/deepseek-r1-distill-llama-70b:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_DEEPSEEK_DEEPSEEK_R1_FREE"] = "deepseek/deepseek-r1:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_GOOGLE_GEMINI_2_0_FLASH_EXP_FREE"] = "google/gemini-2.0-flash-exp:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_META_LLAMA_LLAMA_3_3_70B_INSTRUCT_FREE"] = "meta-llama/llama-3.3-70b-instruct:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_QWEN_QWEN_2_5_CODER_32B_INSTRUCT_FREE"] = "qwen/qwen-2.5-coder-32b-instruct:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_META_LLAMA_LLAMA_3_2_3B_INSTRUCT_FREE"] = "meta-llama/llama-3.2-3b-instruct:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_QWEN_QWEN_2_5_72B_INSTRUCT_FREE"] = "qwen/qwen-2.5-72b-instruct:free"; + E_OPENROUTER_MODEL_FREE["MODEL_FREE_QWEN_QWEN_2_5_VL_7B_INSTRUCT_FREE"] = "qwen/qwen-2.5-vl-7b-instruct:free"; + E_OPENROUTER_MODEL_FREE["MODEL_FREE_NOUSRESEARCH_HERMES_3_LLAMA_3_1_405B_FREE"] = "nousresearch/hermes-3-llama-3.1-405b:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_META_LLAMA_LLAMA_3_1_405B_INSTRUCT_FREE"] = "meta-llama/llama-3.1-405b-instruct:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_MISTRALAI_MISTRAL_NEMO_FREE"] = "mistralai/mistral-nemo:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_GOOGLE_GEMMA_2_9B_IT_FREE"] = "google/gemma-2-9b-it:free"; E_OPENROUTER_MODEL_FREE["MODEL_FREE_MISTRALAI_MISTRAL_7B_INSTRUCT_FREE"] = "mistralai/mistral-7b-instruct:free"; })(E_OPENROUTER_MODEL_FREE || (E_OPENROUTER_MODEL_FREE = {})); -//# 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+//# 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;// ./dist-in/index.js @@ -315261,7 +315295,7 @@ const main_REQUIRE_DIRECTORY_ERROR = 'loading a directory of commands is not sup let main_esm_dirname; try { - main_esm_dirname = (0,main_external_url_.fileURLToPath)("file:///C:/Users/zx/Desktop/polymech/polymech-mono/packages/kbot/node_modules/yargs/lib/platform-shims/esm.mjs"); + main_esm_dirname = (0,main_external_url_.fileURLToPath)("file:///C:/Users/mc007/Desktop/polymech/polymech-mono/packages/kbot/node_modules/yargs/lib/platform-shims/esm.mjs"); } catch (e) { main_esm_dirname = process.cwd(); } @@ -319064,7 +319098,7 @@ var main_openrouter = __webpack_require__(2761); -const main_build_dirname = main_external_node_path_.dirname((0,main_external_node_url_.fileURLToPath)("file:///C:/Users/zx/Desktop/polymech/polymech-mono/packages/kbot/dist-in/commands/build.js")); +const main_build_dirname = main_external_node_path_.dirname((0,main_external_node_url_.fileURLToPath)("file:///C:/Users/mc007/Desktop/polymech/polymech-mono/packages/kbot/dist-in/commands/build.js")); const main_generateModelEnum = (models, provider) => { const enumName = `E_${provider.toUpperCase()}_MODEL`; const enumContent = `export enum ${enumName} { @@ -321479,7 +321513,7 @@ function main_generateUniqueFilename(dst, genFiles) { } function main_getGuiAppPath() { // Get the directory of this script file, then navigate to the GUI app - const scriptDir = main_external_node_path_.dirname(new URL("file:///C:/Users/zx/Desktop/polymech/polymech-mono/packages/kbot/dist-in/commands/images.js").pathname); + const scriptDir = main_external_node_path_.dirname(new URL("file:///C:/Users/mc007/Desktop/polymech/polymech-mono/packages/kbot/dist-in/commands/images.js").pathname); // On Windows, URL.pathname can have an extra leading slash, so we need to handle it const cleanScriptDir = process.platform === 'win32' && scriptDir.startsWith('/') ? scriptDir.substring(1) @@ -322003,8 +322037,8 @@ const main_getVoicesData = async () => { const possiblePaths = [ main_external_node_path_.resolve('src/lib/voices.json'), main_external_node_path_.resolve('lib/voices.json'), - main_external_node_path_.resolve(main_external_node_path_.dirname(new URL("file:///C:/Users/zx/Desktop/polymech/polymech-mono/packages/kbot/dist-in/commands/tts.js").pathname), '..', 'lib', 'voices.json'), - main_external_node_path_.resolve(main_external_node_path_.dirname(new URL("file:///C:/Users/zx/Desktop/polymech/polymech-mono/packages/kbot/dist-in/commands/tts.js").pathname), 'lib', 'voices.json'), + main_external_node_path_.resolve(main_external_node_path_.dirname(new URL("file:///C:/Users/mc007/Desktop/polymech/polymech-mono/packages/kbot/dist-in/commands/tts.js").pathname), '..', 'lib', 'voices.json'), + main_external_node_path_.resolve(main_external_node_path_.dirname(new URL("file:///C:/Users/mc007/Desktop/polymech/polymech-mono/packages/kbot/dist-in/commands/tts.js").pathname), 'lib', 'voices.json'), ]; let voicesContent = ''; for (const voicesPath of possiblePaths) { diff --git a/packages/kbot/dist/package-lock.json b/packages/kbot/dist/package-lock.json index ff629614..78fd33a3 100644 --- a/packages/kbot/dist/package-lock.json +++ b/packages/kbot/dist/package-lock.json @@ -1,12 +1,12 @@ { "name": "@plastichub/kbot", - "version": "1.1.59", + "version": "1.1.60", "lockfileVersion": 3, "requires": true, "packages": { "": { "name": "@plastichub/kbot", - "version": "1.1.59", + "version": "1.1.60", "license": "ISC", "dependencies": { "node-emoji": "^2.2.0" diff --git a/packages/kbot/dist/package.json b/packages/kbot/dist/package.json index 99456b9f..2af4eb46 100644 --- a/packages/kbot/dist/package.json +++ b/packages/kbot/dist/package.json @@ -1,6 +1,6 @@ { "name": "@plastichub/kbot", - "version": "1.1.59", + "version": "1.1.60", "main": "main_node.js", "author": "", "license": "ISC", diff --git a/packages/kbot/dist/win-64/tauri-app.exe b/packages/kbot/dist/win-64/tauri-app.exe index 750134e4..ce39093b 100644 Binary files a/packages/kbot/dist/win-64/tauri-app.exe and b/packages/kbot/dist/win-64/tauri-app.exe differ diff --git a/packages/kbot/gui/tauri-app/src-tauri/Cargo.lock b/packages/kbot/gui/tauri-app/src-tauri/Cargo.lock index d52705e9..8a78a7cc 100644 --- a/packages/kbot/gui/tauri-app/src-tauri/Cargo.lock +++ b/packages/kbot/gui/tauri-app/src-tauri/Cargo.lock @@ -17,41 +17,6 @@ version = "2.0.1" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "320119579fcad9c21884f5c4861d16174d0e06250625266f50fe6898340abefa" -[[package]] -name = "aead" -version = "0.5.2" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "d122413f284cf2d62fb1b7db97e02edb8cda96d769b16e443a4f6195e35662b0" -dependencies = [ - "crypto-common", - "generic-array", -] - -[[package]] -name = "aes" -version = "0.8.4" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "b169f7a6d4742236a0a00c541b845991d0ac43e546831af1249753ab4c3aa3a0" -dependencies = [ - "cfg-if", - "cipher", - "cpufeatures", -] - -[[package]] -name = "aes-gcm" -version = "0.10.3" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "831010a0f742e1209b3bcea8fab6a8e149051ba6099432c8cb2cc117dec3ead1" -dependencies = [ - "aead", - "aes", - "cipher", - "ctr", - "ghash", - "subtle", -] - [[package]] name = "ahash" version = "0.7.8" @@ -784,16 +749,6 @@ dependencies = [ "windows-link 0.2.0", ] -[[package]] -name = "cipher" -version = "0.4.4" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "773f3b9af64447d2ce9850330c473515014aa235e6a783b02db81ff39e4a3dad" -dependencies = [ - "crypto-common", - "inout", -] - [[package]] name = "clap" version = "4.5.48" @@ -1043,7 +998,6 @@ source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "1bfb12502f3fc46cca1bb51ac28df9d618d813cdc3d2f25b9fe775a34af26bb3" dependencies = [ "generic-array", - "rand_core 0.6.4", "typenum", ] @@ -1084,15 +1038,6 @@ dependencies = [ "syn 2.0.106", ] -[[package]] -name = "ctr" -version = "0.9.2" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "0369ee1ad671834580515889b80f2ea915f23b8be8d0daa4bbaf2ac5c7590835" -dependencies = [ - "cipher", -] - [[package]] name = "darling" version = "0.21.3" @@ -1908,16 +1853,6 @@ dependencies = [ "wasm-bindgen", ] -[[package]] -name = "ghash" -version = "0.5.1" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "f0d8a4362ccb29cb0b265253fb0a2728f592895ee6854fd9bc13f2ffda266ff1" -dependencies = [ - "opaque-debug", - "polyval", -] - [[package]] name = "gif" version = "0.13.3" @@ -2514,15 +2449,6 @@ dependencies = [ "cfb", ] -[[package]] -name = "inout" -version = "0.1.4" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "879f10e63c20629ecabbb64a8010319738c66a5cd0c29b02d63d272b03751d01" -dependencies = [ - "generic-array", -] - [[package]] name = "interpolate_name" version = "0.2.4" @@ -3445,12 +3371,6 @@ version = "1.70.1" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "a4895175b425cb1f87721b59f0f286c2092bd4af812243672510e1ac53e2e0ad" -[[package]] -name = "opaque-debug" -version = "0.3.1" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "c08d65885ee38876c4f86fa503fb49d7b507c2b62552df7c70b2fce627e06381" - [[package]] name = "open" version = "5.3.2" @@ -3853,18 +3773,6 @@ dependencies = [ "windows-sys 0.61.0", ] -[[package]] -name = "polyval" -version = "0.6.2" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "9d1fe60d06143b2430aa532c94cfe9e29783047f06c0d7fd359a9a51b729fa25" -dependencies = [ - "cfg-if", - "cpufeatures", - "opaque-debug", - "universal-hash", -] - [[package]] name = "potential_utf" version = "0.1.3" @@ -5390,7 +5298,6 @@ dependencies = [ "tray-icon", "url", "urlpattern", - "uuid", "webkit2gtk", "webview2-com", "window-vibrancy", @@ -5448,7 +5355,6 @@ dependencies = [ "semver", "serde", "serde_json", - "tauri-codegen", "tauri-utils", "tauri-winres", "toml 0.9.7", @@ -5838,13 +5744,11 @@ version = "2.7.0" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "41a3852fdf9a4f8fbeaa63dc3e9a85284dd6ef7200751f0bd66ceee30c93f212" dependencies = [ - "aes-gcm", "anyhow", "brotli", "cargo_metadata", "ctor", "dunce", - "getrandom 0.3.3", "glob", "html5ever", "http", @@ -5863,7 +5767,6 @@ dependencies = [ "serde-untagged", "serde_json", "serde_with", - "serialize-to-javascript", "swift-rs", "thiserror 2.0.16", "toml 0.9.7", @@ -6392,16 +6295,6 @@ version = "1.12.0" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "f6ccf251212114b54433ec949fd6a7841275f9ada20dddd2f29e9ceea4501493" -[[package]] -name = "universal-hash" -version = "0.5.1" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "fc1de2c688dc15305988b563c3854064043356019f97a4b46276fe734c4f07ea" -dependencies = [ - "crypto-common", - "subtle", -] - [[package]] name = "untrusted" version = "0.9.0" diff --git a/packages/kbot/gui/tauri-app/src-tauri/Cargo.toml b/packages/kbot/gui/tauri-app/src-tauri/Cargo.toml index 870cb27a..e5b3d95e 100644 --- a/packages/kbot/gui/tauri-app/src-tauri/Cargo.toml +++ b/packages/kbot/gui/tauri-app/src-tauri/Cargo.toml @@ -15,10 +15,10 @@ name = "tauri_app_lib" crate-type = ["staticlib", "cdylib", "rlib"] [build-dependencies] -tauri-build = { version = "2", features = ["isolation"] } +tauri-build = { version = "2", features = [] } [dependencies] -tauri = { version = "2", features = ["isolation", "macos-private-api", "protocol-asset", "devtools"] } +tauri = { version = "2", features = [ "macos-private-api", "protocol-asset", "devtools"] } tauri-plugin-opener = "2.5.0" tauri-plugin-dialog = "2.4.0" tauri-plugin-fs = "2.0.0" diff --git a/packages/kbot/gui/tauri-app/src-tauri/tauri.conf.json b/packages/kbot/gui/tauri-app/src-tauri/tauri.conf.json index e008a869..b62eff2c 100644 --- a/packages/kbot/gui/tauri-app/src-tauri/tauri.conf.json +++ b/packages/kbot/gui/tauri-app/src-tauri/tauri.conf.json @@ -20,12 +20,6 @@ } ], "security": { - "pattern": { - "use": "isolation", - "options": { - "dir": "../isolation-dist/" - } - }, "csp": { "default-src": "'self' customprotocol: asset:", "script-src": "'self' 'unsafe-inline'", diff --git a/packages/kbot/gui/tauri-app/src/components.css b/packages/kbot/gui/tauri-app/src/components.css index 79ae3493..ef04b22d 100644 --- a/packages/kbot/gui/tauri-app/src/components.css +++ b/packages/kbot/gui/tauri-app/src/components.css @@ -21,11 +21,11 @@ } .dark .glass-card { - @apply backdrop-blur-lg bg-black/10 border-2 border-white/15 shadow-xl rounded-xl; + @apply backdrop-blur-lg bg-white/5 border-2 border-white/20 shadow-2xl rounded-xl; } .dark .glass-card:hover { - @apply border-white/25; + @apply border-white/40 shadow-3xl; } .glass-button { @@ -41,11 +41,11 @@ } .dark .glass-button { - @apply backdrop-blur-md bg-black/10 border-2 border-white/20 hover:bg-black/20 text-white/90 hover:text-white; + @apply backdrop-blur-md bg-white/5 border-2 border-white/30 hover:bg-white/10 text-white hover:text-white shadow-lg; } .dark .glass-button:hover { - @apply border-white/30; + @apply border-white/50 shadow-xl; } .glass-input { @@ -67,13 +67,13 @@ } .dark .glass-input { - @apply backdrop-blur-md bg-slate-800/40 border-2 border-slate-500/80 focus:border-cyan-400/80 text-slate-100 placeholder:text-slate-400; - box-shadow: 0 6px 16px rgba(0, 0, 0, 0.4); + @apply backdrop-blur-md bg-white/5 border-2 border-white/30 focus:border-cyan-400 text-white placeholder:text-slate-300; + box-shadow: 0 6px 16px rgba(0, 0, 0, 0.6); } .dark .glass-input:hover { - @apply border-slate-400/90; - box-shadow: 0 10px 20px rgba(0, 0, 0, 0.5); + @apply border-white/50; + box-shadow: 0 10px 20px rgba(0, 0, 0, 0.7); } .dark .glass-input:focus { @@ -272,4 +272,53 @@ .glass-progress [data-state="complete"] { @apply bg-gradient-to-r from-indigo-500 to-cyan-500; } + + /* High contrast dark mode overrides */ + .dark .text-slate-700 { + color: #ffffff !important; + } + + .dark .text-slate-500 { + color: #e2e8f0 !important; + } + + .dark .text-slate-400 { + color: #cbd5e1 !important; + } + + .dark .text-slate-300 { + color: #ffffff !important; + } + + /* Improve button text contrast */ + .dark .glass-button { + color: #ffffff !important; + } + + /* Improve input text contrast */ + .dark .glass-input { + color: #ffffff !important; + } + + .dark .glass-input::placeholder { + color: #cbd5e1 !important; + } + + /* Improve card backgrounds for better contrast */ + .dark .bg-slate-50\/30 { + background-color: rgba(30, 41, 59, 0.8) !important; + } + + .dark .bg-slate-800\/30 { + background-color: rgba(30, 41, 59, 0.9) !important; + } + + /* Improve border contrast */ + .dark .border-slate-200\/50 { + border-color: rgba(255, 255, 255, 0.2) !important; + } + + .dark .border-slate-700\/50 { + border-color: rgba(255, 255, 255, 0.3) !important; + } } \ No newline at end of file diff --git a/packages/kbot/gui/tauri-app/src/components/Header.tsx b/packages/kbot/gui/tauri-app/src/components/Header.tsx index f0752c94..7397f974 100644 --- a/packages/kbot/gui/tauri-app/src/components/Header.tsx +++ b/packages/kbot/gui/tauri-app/src/components/Header.tsx @@ -1,6 +1,6 @@ -import React from 'react'; +import React, { useState, useEffect, useRef } from 'react'; import { useNavigate } from 'react-router-dom'; -import { T } from '../i18n'; +import { T, getCurrentLang, supportedLanguages } from '../i18n'; interface HeaderProps { showDebugPanel: boolean; @@ -16,6 +16,30 @@ const Header: React.FC = ({ toggleTheme, }) => { const navigate = useNavigate(); + const [showLangDropdown, setShowLangDropdown] = useState(false); + const currentLang = getCurrentLang(); + const dropdownRef = useRef(null); + + const handleLanguageChange = (langCode: string) => { + const currentUrl = window.location.href; + const url = new URL(currentUrl); + url.searchParams.set('lang', langCode); + window.location.href = url.toString(); + }; + + // Close dropdown when clicking outside + useEffect(() => { + const handleClickOutside = (event: MouseEvent) => { + if (dropdownRef.current && !dropdownRef.current.contains(event.target as Node)) { + setShowLangDropdown(false); + } + }; + + document.addEventListener('mousedown', handleClickOutside); + return () => { + document.removeEventListener('mousedown', handleClickOutside); + }; + }, []); return (
{/* Title on its own row */} @@ -30,6 +54,42 @@ const Header: React.FC = ({
{/* Button group - single row */}
+ {/* Language Switcher */} +
+ + + {/* Language Dropdown */} + {showLangDropdown && ( +
+ {supportedLanguages.map((lang) => ( + + ))} +
+ )} +
+ {/* Debug Panel Toggle */}