From afe247e109f26c5b8e5ccdb613665b16fdcce447 Mon Sep 17 00:00:00 2001 From: babayaga Date: Thu, 17 Jul 2025 14:04:20 +0200 Subject: [PATCH] maintainence love:) --- packages/kbot/dist-in/data/openai_models.json | 14 +- .../kbot/dist-in/data/openrouter_models.json | 3598 +++++++++-------- .../kbot/dist-in/src/models/cache/openai.ts | 2 +- .../dist-in/src/models/cache/openrouter.ts | 2 +- packages/kbot/dist/main_node.js | 67 +- packages/kbot/dist/package-lock.json | 4 +- packages/kbot/dist/package.json | 2 +- packages/kbot/extensions/gui/package.json | 4 - .../src/renderer/components/Application.tsx | 7 - .../kbot/src/models/cache/openai-models.ts | 2 - .../models/cache/openrouter-models-free.ts | 14 +- .../src/models/cache/openrouter-models.ts | 71 +- 12 files changed, 2076 insertions(+), 1711 deletions(-) diff --git a/packages/kbot/dist-in/data/openai_models.json b/packages/kbot/dist-in/data/openai_models.json index ed5209c3..c5829484 100644 --- a/packages/kbot/dist-in/data/openai_models.json +++ b/packages/kbot/dist-in/data/openai_models.json @@ -1,5 +1,5 @@ { - "timestamp": 1751652874753, + "timestamp": 1752753846841, "models": [ { "id": "gpt-4-0613", @@ -319,18 +319,6 @@ "created": 1739331543, "owned_by": "system" }, - { - "id": "gpt-4.5-preview", - "object": "model", - "created": 1740623059, - "owned_by": "system" - }, - { - "id": "gpt-4.5-preview-2025-02-27", - "object": "model", - "created": 1740623304, - "owned_by": "system" - }, { "id": "gpt-4o-search-preview-2025-03-11", "object": "model", diff --git a/packages/kbot/dist-in/data/openrouter_models.json b/packages/kbot/dist-in/data/openrouter_models.json index d8bf0843..269e801e 100644 --- a/packages/kbot/dist-in/data/openrouter_models.json +++ b/packages/kbot/dist-in/data/openrouter_models.json @@ -1,14 +1,58 @@ { - "timestamp": 1751652875009, + "timestamp": 1752753847193, "models": [ { - "id": "openrouter/cypher-alpha:free", - "canonical_slug": "openrouter/cypher-alpha", + "id": "switchpoint/router", + "canonical_slug": "switchpoint/router", "hugging_face_id": "", - "name": "Cypher Alpha (free)", - "created": 1751336087, - "description": "This is a cloaked model provided to the community to gather feedback. It's an all-purpose model supporting real-world, long-context tasks including code generation.\n\nNote: All prompts and completions for this model are logged by the provider and may be used to improve the model and other products and services. You remain responsible for any required end user notices and consents and for ensuring that no personal, confidential, or otherwise sensitive information, including data from individuals under the age of 18, is submitted.", - "context_length": 1000000, + "name": "Switchpoint Router", + "created": 1752272899, + "description": "Switchpoint AI's router instantly analyzes your request and directs it to the optimal AI from an ever-evolving library. \n\nAs the world of LLMs advances, our router gets smarter, ensuring you always benefit from the industry's newest models without changing your workflow.\n\nThis model is configured for a simple, flat rate per response here on OpenRouter. It's powered by the full routing engine from [Switchpoint AI](https://www.switchpoint.dev).", + "context_length": 131072, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Other", + "instruct_type": null + }, + "pricing": { + "prompt": "0.00000085", + "completion": "0.0000034", + "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": [ + "max_tokens", + "temperature", + "top_p", + "reasoning", + "include_reasoning", + "stop", + "top_k", + "seed" + ] + }, + { + "id": "moonshotai/kimi-k2:free", + "canonical_slug": "moonshotai/kimi-k2", + "hugging_face_id": "moonshotai/Kimi-K2-Instruct", + "name": "MoonshotAI: Kimi K2 (free)", + "created": 1752263252, + "description": "Kimi K2 Instruct is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32 billion active per forward pass. It is optimized for agentic capabilities, including advanced tool use, reasoning, and code synthesis. Kimi K2 excels across a broad range of benchmarks, particularly in coding (LiveCodeBench, SWE-bench), reasoning (ZebraLogic, GPQA), and tool-use (Tau2, AceBench) tasks. It supports long-context inference up to 128K tokens and is designed with a novel training stack that includes the MuonClip optimizer for stable large-scale MoE training.", + "context_length": 65536, "architecture": { "modality": "text->text", "input_modalities": [ @@ -29,8 +73,306 @@ "internal_reasoning": "0" }, "top_provider": { - "context_length": 1000000, - "max_completion_tokens": 10000, + "context_length": 65536, + "max_completion_tokens": null, + "is_moderated": false + }, + "per_request_limits": null, + "supported_parameters": [ + "max_tokens", + "temperature", + "top_p", + "tools", + "tool_choice", + "stop", + "frequency_penalty", + "presence_penalty", + "seed", + "top_k", + "min_p", + "repetition_penalty", + "logprobs", + "logit_bias", + "top_logprobs" + ] + }, + { + "id": "moonshotai/kimi-k2", + "canonical_slug": "moonshotai/kimi-k2", + "hugging_face_id": "moonshotai/Kimi-K2-Instruct", + "name": "MoonshotAI: Kimi K2", + "created": 1752263252, + "description": "Kimi K2 Instruct is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32 billion active per forward pass. It is optimized for agentic capabilities, including advanced tool use, reasoning, and code synthesis. Kimi K2 excels across a broad range of benchmarks, particularly in coding (LiveCodeBench, SWE-bench), reasoning (ZebraLogic, GPQA), and tool-use (Tau2, AceBench) tasks. It supports long-context inference up to 128K tokens and is designed with a novel training stack that includes the MuonClip optimizer for stable large-scale MoE training.", + "context_length": 63000, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Other", + "instruct_type": null + }, + "pricing": { + "prompt": "0.00000014", + "completion": "0.00000249", + "request": "0", + "image": "0", + "web_search": "0", + "internal_reasoning": "0" + }, + "top_provider": { + "context_length": 63000, + "max_completion_tokens": 63000, + "is_moderated": false + }, + "per_request_limits": null, + "supported_parameters": [ + "max_tokens", + "temperature", + "top_p", + "tools", + "tool_choice", + "structured_outputs", + "response_format", + "stop", + "frequency_penalty", + "presence_penalty", + "top_k", + "repetition_penalty", + "logit_bias", + "min_p", + "seed", + "top_logprobs", + "logprobs" + ] + }, + { + "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": "0.000000035", + "completion": "0.000000138", + "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": [ + "max_tokens", + "temperature", + "top_p", + "reasoning", + "include_reasoning", + "stop", + "frequency_penalty", + "presence_penalty", + "seed", + "top_k", + "min_p", + "repetition_penalty", + "logit_bias" + ] + }, + { + "id": "mistralai/devstral-medium", + "canonical_slug": "mistralai/devstral-medium-2507", + "hugging_face_id": "", + "name": "Mistral: Devstral Medium", + "created": 1752161321, + "description": "Devstral Medium is a high-performance code generation and agentic reasoning model developed jointly by Mistral AI and All Hands AI. Positioned as a step up from Devstral Small, it achieves 61.6% on SWE-Bench Verified, placing it ahead of Gemini 2.5 Pro and GPT-4.1 in code-related tasks, at a fraction of the cost. It is designed for generalization across prompt styles and tool use in code agents and frameworks.\n\nDevstral Medium is available via API only (not open-weight), and supports enterprise deployment on private infrastructure, with optional fine-tuning capabilities.", + "context_length": 131072, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Mistral", + "instruct_type": null + }, + "pricing": { + "prompt": "0.0000004", + "completion": "0.000002", + "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": [ + "max_tokens", + "temperature", + "top_p", + "tools", + "tool_choice", + "stop", + "frequency_penalty", + "presence_penalty", + "response_format", + "structured_outputs", + "seed" + ] + }, + { + "id": "mistralai/devstral-small", + "canonical_slug": "mistralai/devstral-small-2507", + "hugging_face_id": "mistralai/Devstral-Small-2507", + "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, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Mistral", + "instruct_type": null + }, + "pricing": { + "prompt": "0.00000007", + "completion": "0.00000028", + "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", + "top_p", + "tools", + "tool_choice", + "stop", + "frequency_penalty", + "presence_penalty", + "response_format", + "structured_outputs", + "seed", + "min_p", + "repetition_penalty", + "top_k" + ] + }, + { + "id": "cognitivecomputations/dolphin-mistral-24b-venice-edition:free", + "canonical_slug": "venice/uncensored", + "hugging_face_id": "cognitivecomputations/Dolphin-Mistral-24B-Venice-Edition", + "name": "Venice: Uncensored (free)", + "created": 1752094966, + "description": "Venice Uncensored Dolphin Mistral 24B Venice Edition is a fine-tuned variant of Mistral-Small-24B-Instruct-2501, developed by dphn.ai in collaboration with Venice.ai. This model is designed as an “uncensored” instruct-tuned LLM, preserving user control over alignment, system prompts, and behavior. Intended for advanced and unrestricted use cases, Venice Uncensored emphasizes steerability and transparent behavior, removing default safety and alignment layers typically found in mainstream assistant models.", + "context_length": 32768, + "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": 32768, + "max_completion_tokens": null, + "is_moderated": false + }, + "per_request_limits": null, + "supported_parameters": [ + "max_tokens", + "temperature", + "top_p", + "structured_outputs", + "response_format", + "stop", + "frequency_penalty", + "presence_penalty", + "top_k" + ] + }, + { + "id": "x-ai/grok-4", + "canonical_slug": "x-ai/grok-4-07-09", + "hugging_face_id": "", + "name": "xAI: Grok 4", + "created": 1752087689, + "description": "Grok 4 is xAI's latest reasoning model with a 256k context window. It supports parallel tool calling, structured outputs, and both image and text inputs. Note that reasoning is not exposed, reasoning cannot be disabled, and the reasoning effort cannot be specified. Pricing increases once the total tokens in a given request is greater than 128k tokens. See more details on the [xAI docs](https://docs.x.ai/docs/models/grok-4-0709)", + "context_length": 256000, + "architecture": { + "modality": "text+image->text", + "input_modalities": [ + "image", + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Grok", + "instruct_type": null + }, + "pricing": { + "prompt": "0.000003", + "completion": "0.000015", + "request": "0", + "image": "0", + "web_search": "0", + "internal_reasoning": "0", + "input_cache_read": "0.00000075" + }, + "top_provider": { + "context_length": 256000, + "max_completion_tokens": null, "is_moderated": false }, "per_request_limits": null, @@ -41,9 +383,281 @@ "tools", "tool_choice", "reasoning", - "include_reasoning" + "include_reasoning", + "structured_outputs", + "seed", + "logprobs", + "top_logprobs", + "response_format" ] }, + { + "id": "google/gemma-3n-e2b-it:free", + "canonical_slug": "google/gemma-3n-e2b-it", + "hugging_face_id": "google/gemma-3n-E2B-it", + "name": "Google: Gemma 3n 2B (free)", + "created": 1752074904, + "description": "Gemma 3n E2B IT is a multimodal, instruction-tuned model developed by Google DeepMind, designed to operate efficiently at an effective parameter size of 2B while leveraging a 6B architecture. Based on the MatFormer architecture, it supports nested submodels and modular composition via the Mix-and-Match framework. Gemma 3n models are optimized for low-resource deployment, offering 32K context length and strong multilingual and reasoning performance across common benchmarks. This variant is trained on a diverse corpus including code, math, web, and multimodal data.", + "context_length": 8192, + "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": 8192, + "max_completion_tokens": 2048, + "is_moderated": false + }, + "per_request_limits": null, + "supported_parameters": [ + "max_tokens", + "temperature", + "top_p", + "stop", + "frequency_penalty", + "presence_penalty", + "seed", + "response_format" + ] + }, + { + "id": "tencent/hunyuan-a13b-instruct:free", + "canonical_slug": "tencent/hunyuan-a13b-instruct", + "hugging_face_id": "tencent/Hunyuan-A13B-Instruct", + "name": "Tencent: Hunyuan A13B Instruct (free)", + "created": 1751987664, + "description": "Hunyuan-A13B is a 13B active parameter Mixture-of-Experts (MoE) language model developed by Tencent, with a total parameter count of 80B and support for reasoning via Chain-of-Thought. It offers competitive benchmark performance across mathematics, science, coding, and multi-turn reasoning tasks, while maintaining high inference efficiency via Grouped Query Attention (GQA) and quantization support (FP8, GPTQ, etc.).", + "context_length": 32768, + "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": 32768, + "max_completion_tokens": null, + "is_moderated": false + }, + "per_request_limits": null, + "supported_parameters": [ + "max_tokens", + "temperature", + "top_p", + "reasoning", + "include_reasoning", + "stop", + "frequency_penalty", + "presence_penalty", + "seed", + "top_k", + "min_p", + "repetition_penalty", + "logprobs", + "logit_bias", + "top_logprobs" + ] + }, + { + "id": "tencent/hunyuan-a13b-instruct", + "canonical_slug": "tencent/hunyuan-a13b-instruct", + "hugging_face_id": "tencent/Hunyuan-A13B-Instruct", + "name": "Tencent: Hunyuan A13B Instruct", + "created": 1751987664, + "description": "Hunyuan-A13B is a 13B active parameter Mixture-of-Experts (MoE) language model developed by Tencent, with a total parameter count of 80B and support for reasoning via Chain-of-Thought. It offers competitive benchmark performance across mathematics, science, coding, and multi-turn reasoning tasks, while maintaining high inference efficiency via Grouped Query Attention (GQA) and quantization support (FP8, GPTQ, etc.).", + "context_length": 32768, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Other", + "instruct_type": null + }, + "pricing": { + "prompt": "0.00000003", + "completion": "0.00000003", + "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": [ + "max_tokens", + "temperature", + "top_p", + "reasoning", + "include_reasoning", + "stop", + "frequency_penalty", + "presence_penalty", + "seed", + "top_k", + "min_p", + "repetition_penalty", + "logprobs", + "logit_bias", + "top_logprobs" + ] + }, + { + "id": "tngtech/deepseek-r1t2-chimera:free", + "canonical_slug": "tngtech/deepseek-r1t2-chimera", + "hugging_face_id": "tngtech/DeepSeek-TNG-R1T2-Chimera", + "name": "TNG: DeepSeek R1T2 Chimera (free)", + "created": 1751986985, + "description": "DeepSeek-TNG-R1T2-Chimera is the second-generation Chimera model from TNG Tech. It is a 671 B-parameter mixture-of-experts text-generation model assembled from DeepSeek-AI’s R1-0528, R1, and V3-0324 checkpoints with an Assembly-of-Experts merge. The tri-parent design yields strong reasoning performance while running roughly 20 % faster than the original R1 and more than 2× faster than R1-0528 under vLLM, giving a favorable cost-to-intelligence trade-off. The checkpoint supports contexts up to 60 k tokens in standard use (tested to ~130 k) and maintains consistent token behaviour, making it suitable for long-context analysis, dialogue and other open-ended generation tasks.", + "context_length": 163840, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "DeepSeek", + "instruct_type": null + }, + "pricing": { + "prompt": "0", + "completion": "0", + "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": [ + "max_tokens", + "temperature", + "top_p", + "reasoning", + "include_reasoning", + "stop", + "frequency_penalty", + "presence_penalty", + "seed", + "top_k", + "min_p", + "repetition_penalty", + "logprobs", + "logit_bias", + "top_logprobs" + ] + }, + { + "id": "morph/morph-v3-large", + "canonical_slug": "morph/morph-v3-large", + "hugging_face_id": "", + "name": "Morph: Morph V3 Large", + "created": 1751910858, + "description": "Morph's high-accuracy apply model for complex code edits. 2000+ tokens/sec with 98% accuracy for precise code transformations.", + "context_length": 32000, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Other", + "instruct_type": null + }, + "pricing": { + "prompt": "0.0000012", + "completion": "0.0000027", + "request": "0", + "image": "0", + "web_search": "0", + "internal_reasoning": "0" + }, + "top_provider": { + "context_length": 32000, + "max_completion_tokens": 16000, + "is_moderated": false + }, + "per_request_limits": null, + "supported_parameters": [] + }, + { + "id": "morph/morph-v3-fast", + "canonical_slug": "morph/morph-v3-fast", + "hugging_face_id": "", + "name": "Morph: Morph V3 Fast", + "created": 1751910002, + "description": "Morph's fastest apply model for code edits. 4500+ tokens/sec with 96% accuracy for rapid code transformations.", + "context_length": 32000, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Other", + "instruct_type": null + }, + "pricing": { + "prompt": "0.0000012", + "completion": "0.0000027", + "request": "0", + "image": "0", + "web_search": "0", + "internal_reasoning": "0" + }, + "top_provider": { + "context_length": 32000, + "max_completion_tokens": 16000, + "is_moderated": false + }, + "per_request_limits": null, + "supported_parameters": [] + }, { "id": "baidu/ernie-4.5-300b-a47b", "canonical_slug": "baidu/ernie-4.5-300b-a47b", @@ -111,7 +725,7 @@ "instruct_type": null }, "pricing": { - "prompt": "0.0000003", + "prompt": "0.0000005", "completion": "0.0000008", "request": "0", "image": "0", @@ -128,9 +742,12 @@ "max_tokens", "temperature", "top_p", - "presence_penalty", "frequency_penalty", + "min_p", + "presence_penalty", "repetition_penalty", + "seed", + "stop", "top_k" ] }, @@ -300,15 +917,17 @@ "max_tokens", "temperature", "top_p", - "tools", - "tool_choice", "stop", "frequency_penalty", "presence_penalty", - "response_format", - "structured_outputs", + "logit_bias", + "logprobs", "seed", "repetition_penalty", + "tools", + "tool_choice", + "response_format", + "structured_outputs", "top_k", "min_p" ] @@ -392,7 +1011,9 @@ "request": "0", "image": "0", "web_search": "0", - "internal_reasoning": "0" + "internal_reasoning": "0", + "input_cache_read": "0.000000025", + "input_cache_write": "0.0000001833" }, "top_provider": { "context_length": 1048576, @@ -406,9 +1027,11 @@ "top_p", "tools", "tool_choice", - "stop", + "reasoning", + "include_reasoning", + "structured_outputs", "response_format", - "structured_outputs" + "stop" ] }, { @@ -454,9 +1077,11 @@ "top_p", "tools", "tool_choice", - "stop", + "reasoning", + "include_reasoning", + "structured_outputs", "response_format", - "structured_outputs" + "stop" ] }, { @@ -502,9 +1127,11 @@ "top_p", "tools", "tool_choice", - "stop", + "reasoning", + "include_reasoning", + "structured_outputs", "response_format", - "structured_outputs" + "stop" ] }, { @@ -709,7 +1336,7 @@ "name": "Mistral: Magistral Small 2506", "created": 1749569561, "description": "Magistral Small is a 24B parameter instruction-tuned model based on Mistral-Small-3.1 (2503), enhanced through supervised fine-tuning on traces from Magistral Medium and further refined via reinforcement learning. It is optimized for reasoning and supports a wide multilingual range, including over 20 languages.", - "context_length": 40000, + "context_length": 40960, "architecture": { "modality": "text->text", "input_modalities": [ @@ -722,16 +1349,16 @@ "instruct_type": null }, "pricing": { - "prompt": "0.0000005", - "completion": "0.0000015", + "prompt": "0.0000001", + "completion": "0.0000003", "request": "0", "image": "0", "web_search": "0", "internal_reasoning": "0" }, "top_provider": { - "context_length": 40000, - "max_completion_tokens": 40000, + "context_length": 40960, + "max_completion_tokens": 40960, "is_moderated": false }, "per_request_limits": null, @@ -739,16 +1366,22 @@ "max_tokens", "temperature", "top_p", - "tools", - "tool_choice", "reasoning", "include_reasoning", - "structured_outputs", - "response_format", "stop", "frequency_penalty", "presence_penalty", - "seed" + "top_k", + "repetition_penalty", + "logit_bias", + "logprobs", + "top_logprobs", + "min_p", + "seed", + "tools", + "tool_choice", + "structured_outputs", + "response_format" ] }, { @@ -892,9 +1525,11 @@ "top_p", "tools", "tool_choice", - "stop", + "reasoning", + "include_reasoning", + "structured_outputs", "response_format", - "structured_outputs" + "stop" ] }, { @@ -1029,13 +1664,13 @@ "top_p", "reasoning", "include_reasoning", - "presence_penalty", "frequency_penalty", - "repetition_penalty", - "top_k", - "stop", - "seed", "min_p", + "presence_penalty", + "repetition_penalty", + "seed", + "stop", + "top_k", "logit_bias" ] }, @@ -1088,8 +1723,8 @@ "logprobs", "logit_bias", "top_logprobs", - "response_format", - "top_a" + "structured_outputs", + "response_format" ] }, { @@ -1099,7 +1734,7 @@ "name": "DeepSeek: R1 0528", "created": 1748455170, "description": "May 28th update to the [original DeepSeek R1](/deepseek/deepseek-r1) 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.", - "context_length": 128000, + "context_length": 163840, "architecture": { "modality": "text->text", "input_modalities": [ @@ -1112,16 +1747,16 @@ "instruct_type": "deepseek-r1" }, "pricing": { - "prompt": "0.0000005", - "completion": "0.00000215", + "prompt": "0.000000272", + "completion": "0.000000272", "request": "0", "image": "0", "web_search": "0", "internal_reasoning": "0" }, "top_provider": { - "context_length": 128000, - "max_completion_tokens": 32768, + "context_length": 163840, + "max_completion_tokens": null, "is_moderated": false }, "per_request_limits": null, @@ -1139,12 +1774,12 @@ "logit_bias", "min_p", "response_format", - "logprobs", - "top_logprobs", - "seed", "tools", "tool_choice", - "structured_outputs" + "structured_outputs", + "seed", + "logprobs", + "top_logprobs" ] }, { @@ -1197,13 +1832,13 @@ ] }, { - "id": "thedrummer/valkyrie-49b-v1", - "canonical_slug": "thedrummer/valkyrie-49b-v1", - "hugging_face_id": "TheDrummer/Valkyrie-49B-v1", - "name": "TheDrummer: Valkyrie 49B V1", - "created": 1748022670, - "description": "Built on top of NVIDIA's Llama 3.3 Nemotron Super 49B, Valkyrie is TheDrummer's newest model drop for creative writing.", - "context_length": 131072, + "id": "sarvamai/sarvam-m", + "canonical_slug": "sarvamai/sarvam-m", + "hugging_face_id": "sarvamai/sarvam-m", + "name": "Sarvam AI: Sarvam-M", + "created": 1748188413, + "description": "Sarvam-M is a 24 B-parameter, instruction-tuned derivative of Mistral-Small-3.1-24B-Base-2503, post-trained on English plus eleven major Indic languages (bn, hi, kn, gu, mr, ml, or, pa, ta, te). The model introduces a dual-mode interface: “non-think” for low-latency chat and a optional “think” phase that exposes chain-of-thought tokens for more demanding reasoning, math, and coding tasks. \n\nBenchmark reports show solid gains versus similarly sized open models on Indic-language QA, GSM-8K math, and SWE-Bench coding, making Sarvam-M a practical general-purpose choice for multilingual conversational agents as well as analytical workloads that mix English, native Indic scripts, or romanized text.", + "context_length": 32768, "architecture": { "modality": "text->text", "input_modalities": [ @@ -1216,16 +1851,16 @@ "instruct_type": null }, "pricing": { - "prompt": "0.0000005", - "completion": "0.0000008", + "prompt": "0.000000022", + "completion": "0.000000022", "request": "0", "image": "0", "web_search": "0", "internal_reasoning": "0" }, "top_provider": { - "context_length": 131072, - "max_completion_tokens": 131072, + "context_length": 32768, + "max_completion_tokens": null, "is_moderated": false }, "per_request_limits": null, @@ -1233,11 +1868,65 @@ "max_tokens", "temperature", "top_p", + "stop", + "frequency_penalty", + "presence_penalty", + "seed", + "top_k", + "min_p", + "repetition_penalty", + "logprobs", + "logit_bias", + "top_logprobs" + ] + }, + { + "id": "thedrummer/valkyrie-49b-v1", + "canonical_slug": "thedrummer/valkyrie-49b-v1", + "hugging_face_id": "TheDrummer/Valkyrie-49B-v1", + "name": "TheDrummer: Valkyrie 49B V1", + "created": 1748022670, + "description": "Built on top of NVIDIA's Llama 3.3 Nemotron Super 49B, Valkyrie is TheDrummer's newest model drop for creative writing.", + "context_length": 32768, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Other", + "instruct_type": null + }, + "pricing": { + "prompt": "0.0000006", + "completion": "0.0000008", + "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": [ + "max_tokens", + "temperature", + "top_p", + "stop", + "frequency_penalty", + "presence_penalty", + "response_format", + "structured_outputs", "reasoning", "include_reasoning", - "presence_penalty", - "frequency_penalty", + "min_p", "repetition_penalty", + "seed", "top_k" ] }, @@ -1338,10 +2027,10 @@ ] }, { - "id": "mistralai/devstral-small:free", + "id": "mistralai/devstral-small-2505:free", "canonical_slug": "mistralai/devstral-small-2505", "hugging_face_id": "mistralai/Devstral-Small-2505", - "name": "Mistral: Devstral Small (free)", + "name": "Mistral: Devstral Small 2505 (free)", "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": 32768, @@ -1353,7 +2042,7 @@ "output_modalities": [ "text" ], - "tokenizer": "Other", + "tokenizer": "Mistral", "instruct_type": null }, "pricing": { @@ -1389,13 +2078,13 @@ ] }, { - "id": "mistralai/devstral-small", + "id": "mistralai/devstral-small-2505", "canonical_slug": "mistralai/devstral-small-2505", "hugging_face_id": "mistralai/Devstral-Small-2505", - "name": "Mistral: Devstral Small", + "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, + "context_length": 32768, "architecture": { "modality": "text->text", "input_modalities": [ @@ -1404,19 +2093,19 @@ "output_modalities": [ "text" ], - "tokenizer": "Other", + "tokenizer": "Mistral", "instruct_type": null }, "pricing": { - "prompt": "0.00000006", - "completion": "0.00000012", + "prompt": "0.00000003", + "completion": "0.00000003", "request": "0", "image": "0", "web_search": "0", "internal_reasoning": "0" }, "top_provider": { - "context_length": 128000, + "context_length": 32768, "max_completion_tokens": null, "is_moderated": false }, @@ -1532,102 +2221,6 @@ "response_format" ] }, - { - "id": "google/gemini-2.5-flash-preview-05-20", - "canonical_slug": "google/gemini-2.5-flash-preview-05-20", - "hugging_face_id": "", - "name": "Google: Gemini 2.5 Flash Preview 05-20", - "created": 1747761924, - "description": "Gemini 2.5 Flash May 20th 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\nNote: This model is available in two variants: thinking and non-thinking. The output pricing varies significantly depending on whether the thinking capability is active. If you select the standard variant (without the \":thinking\" suffix), the model will explicitly avoid generating thinking tokens. \n\nTo utilize the thinking capability and receive thinking tokens, you must choose the \":thinking\" variant, which will then incur the higher thinking-output pricing. \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", - "input_modalities": [ - "image", - "text", - "file" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Gemini", - "instruct_type": null - }, - "pricing": { - "prompt": "0.00000015", - "completion": "0.0000006", - "request": "0", - "image": "0.0006192", - "web_search": "0", - "internal_reasoning": "0", - "input_cache_read": "0.0000000375", - "input_cache_write": "0.0000002333" - }, - "top_provider": { - "context_length": 1048576, - "max_completion_tokens": 65535, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "max_tokens", - "temperature", - "top_p", - "tools", - "tool_choice", - "stop", - "response_format", - "structured_outputs" - ] - }, - { - "id": "google/gemini-2.5-flash-preview-05-20:thinking", - "canonical_slug": "google/gemini-2.5-flash-preview-05-20", - "hugging_face_id": "", - "name": "Google: Gemini 2.5 Flash Preview 05-20 (thinking)", - "created": 1747761924, - "description": "Gemini 2.5 Flash May 20th 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\nNote: This model is available in two variants: thinking and non-thinking. The output pricing varies significantly depending on whether the thinking capability is active. If you select the standard variant (without the \":thinking\" suffix), the model will explicitly avoid generating thinking tokens. \n\nTo utilize the thinking capability and receive thinking tokens, you must choose the \":thinking\" variant, which will then incur the higher thinking-output pricing. \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", - "input_modalities": [ - "image", - "text", - "file" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Gemini", - "instruct_type": null - }, - "pricing": { - "prompt": "0.00000015", - "completion": "0.0000035", - "request": "0", - "image": "0.0006192", - "web_search": "0", - "internal_reasoning": "0", - "input_cache_read": "0.0000000375", - "input_cache_write": "0.0000002333" - }, - "top_provider": { - "context_length": 1048576, - "max_completion_tokens": 65535, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "max_tokens", - "temperature", - "top_p", - "tools", - "tool_choice", - "stop", - "response_format", - "structured_outputs" - ] - }, { "id": "openai/codex-mini", "canonical_slug": "openai/codex-mini", @@ -1763,10 +2356,12 @@ "top_p", "tools", "tool_choice", - "stop", - "seed", + "reasoning", + "include_reasoning", + "structured_outputs", "response_format", - "structured_outputs" + "stop", + "seed" ] }, { @@ -2160,7 +2755,7 @@ "hugging_face_id": "", "name": "Inception: Mercury Coder", "created": 1746033880, - "description": "Mercury Coder Small is the first diffusion large language model (dLLM). Applying a breakthrough discrete diffusion approach, the model runs 5-10x faster than even speed optimized models like Claude 3.5 Haiku and GPT-4o Mini while matching their performance. Mercury Coder Small's speed means that developers can stay in the flow while coding, enjoying rapid chat-based iteration and responsive code completion suggestions. On Copilot Arena, Mercury Coder ranks 1st in speed and ties for 2nd in quality. Read more in the [blog post here](https://www.inceptionlabs.ai/introducing-mercury).", + "description": "Mercury Coder is the first diffusion large language model (dLLM). Applying a breakthrough discrete diffusion approach, the model runs 5-10x faster than even speed optimized models like Claude 3.5 Haiku and GPT-4o Mini while matching their performance. Mercury Coder's speed means that developers can stay in the flow while coding, enjoying rapid chat-based iteration and responsive code completion suggestions. On Copilot Arena, Mercury Coder ranks 1st in speed and ties for 2nd in quality. Read more in the [blog post here](https://www.inceptionlabs.ai/introducing-mercury).", "context_length": 32000, "architecture": { "modality": "text->text", @@ -2194,6 +2789,55 @@ "stop" ] }, + { + "id": "qwen/qwen3-4b:free", + "canonical_slug": "qwen/qwen3-4b-04-28", + "hugging_face_id": "Qwen/Qwen3-4B", + "name": "Qwen: Qwen3 4B (free)", + "created": 1746031104, + "description": "Qwen3-4B is a 4 billion parameter dense language model from the Qwen3 series, designed to support both general-purpose and reasoning-intensive tasks. It introduces a dual-mode architecture—thinking and non-thinking—allowing dynamic switching between high-precision logical reasoning and efficient dialogue generation. This makes it well-suited for multi-turn chat, instruction following, and complex agent workflows.", + "context_length": 40960, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Qwen3", + "instruct_type": "qwen3" + }, + "pricing": { + "prompt": "0", + "completion": "0", + "request": "0", + "image": "0", + "web_search": "0", + "internal_reasoning": "0" + }, + "top_provider": { + "context_length": 40960, + "max_completion_tokens": null, + "is_moderated": false + }, + "per_request_limits": null, + "supported_parameters": [ + "max_tokens", + "temperature", + "top_p", + "tools", + "tool_choice", + "reasoning", + "include_reasoning", + "structured_outputs", + "response_format", + "stop", + "frequency_penalty", + "presence_penalty", + "top_k" + ] + }, { "id": "opengvlab/internvl3-14b", "canonical_slug": "opengvlab/internvl3-14b", @@ -2241,7 +2885,7 @@ "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": 131072, + "context_length": 163840, "architecture": { "modality": "text->text", "input_modalities": [ @@ -2262,7 +2906,7 @@ "internal_reasoning": "0" }, "top_provider": { - "context_length": 131072, + "context_length": 163840, "max_completion_tokens": null, "is_moderated": false }, @@ -2274,12 +2918,11 @@ "stop", "frequency_penalty", "presence_penalty", - "seed", - "top_k", - "min_p", "repetition_penalty", - "logit_bias", - "response_format" + "response_format", + "top_k", + "seed", + "min_p" ] }, { @@ -2323,14 +2966,14 @@ "stop", "frequency_penalty", "presence_penalty", - "top_k", "repetition_penalty", - "logit_bias", - "min_p", "response_format", + "top_k", "seed", + "min_p", "top_logprobs", - "logprobs" + "logprobs", + "logit_bias" ] }, { @@ -2629,16 +3272,16 @@ "top_p", "reasoning", "include_reasoning", - "presence_penalty", "frequency_penalty", + "min_p", + "presence_penalty", "repetition_penalty", + "seed", + "stop", "top_k", "tools", "tool_choice", - "stop", "response_format", - "seed", - "min_p", "logit_bias", "logprobs", "top_logprobs" @@ -2744,10 +3387,10 @@ "seed", "tools", "tool_choice", - "repetition_penalty", + "structured_outputs", "top_k", "min_p", - "structured_outputs" + "repetition_penalty" ] }, { @@ -2757,7 +3400,7 @@ "name": "Qwen: Qwen3 235B A22B (free)", "created": 1745875757, "description": "Qwen3-235B-A22B is a 235B parameter mixture-of-experts (MoE) model developed by Qwen, activating 22B parameters per forward pass. It supports seamless switching between a \"thinking\" mode for complex reasoning, math, and code tasks, and a \"non-thinking\" mode for general conversational efficiency. The model demonstrates strong reasoning ability, multilingual support (100+ languages and dialects), advanced instruction-following, and agent tool-calling capabilities. It natively handles a 32K token context window and extends up to 131K tokens using YaRN-based scaling.", - "context_length": 40960, + "context_length": 131072, "architecture": { "modality": "text->text", "input_modalities": [ @@ -2778,7 +3421,7 @@ "internal_reasoning": "0" }, "top_provider": { - "context_length": 40960, + "context_length": 131072, "max_completion_tokens": null, "is_moderated": false }, @@ -2787,13 +3430,17 @@ "max_tokens", "temperature", "top_p", - "reasoning", - "include_reasoning", + "tools", + "tool_choice", + "structured_outputs", + "response_format", "stop", "frequency_penalty", "presence_penalty", - "seed", "top_k", + "reasoning", + "include_reasoning", + "seed", "min_p", "repetition_penalty", "logprobs", @@ -2838,22 +3485,22 @@ "max_tokens", "temperature", "top_p", - "reasoning", - "include_reasoning", - "seed", - "presence_penalty", - "frequency_penalty", - "repetition_penalty", - "top_k", "tools", "tool_choice", - "stop", - "response_format", + "reasoning", + "include_reasoning", "structured_outputs", - "logit_bias", + "response_format", + "stop", + "frequency_penalty", + "presence_penalty", + "seed", + "top_k", + "min_p", + "repetition_penalty", "logprobs", "top_logprobs", - "min_p" + "logit_bias" ] }, { @@ -3105,102 +3752,6 @@ "logit_bias" ] }, - { - "id": "google/gemini-2.5-flash-preview", - "canonical_slug": "google/gemini-2.5-flash-preview-04-17", - "hugging_face_id": "", - "name": "Google: Gemini 2.5 Flash Preview 04-17", - "created": 1744914667, - "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\nNote: This model is available in two variants: thinking and non-thinking. The output pricing varies significantly depending on whether the thinking capability is active. If you select the standard variant (without the \":thinking\" suffix), the model will explicitly avoid generating thinking tokens. \n\nTo utilize the thinking capability and receive thinking tokens, you must choose the \":thinking\" variant, which will then incur the higher thinking-output pricing. \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", - "input_modalities": [ - "image", - "text", - "file" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Gemini", - "instruct_type": null - }, - "pricing": { - "prompt": "0.00000015", - "completion": "0.0000006", - "request": "0", - "image": "0.0006192", - "web_search": "0", - "internal_reasoning": "0", - "input_cache_read": "0.0000000375", - "input_cache_write": "0.0000002333" - }, - "top_provider": { - "context_length": 1048576, - "max_completion_tokens": 65535, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "max_tokens", - "temperature", - "top_p", - "tools", - "tool_choice", - "stop", - "response_format", - "structured_outputs" - ] - }, - { - "id": "google/gemini-2.5-flash-preview:thinking", - "canonical_slug": "google/gemini-2.5-flash-preview-04-17", - "hugging_face_id": "", - "name": "Google: Gemini 2.5 Flash Preview 04-17 (thinking)", - "created": 1744914667, - "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\nNote: This model is available in two variants: thinking and non-thinking. The output pricing varies significantly depending on whether the thinking capability is active. If you select the standard variant (without the \":thinking\" suffix), the model will explicitly avoid generating thinking tokens. \n\nTo utilize the thinking capability and receive thinking tokens, you must choose the \":thinking\" variant, which will then incur the higher thinking-output pricing. \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", - "input_modalities": [ - "image", - "text", - "file" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Gemini", - "instruct_type": null - }, - "pricing": { - "prompt": "0.00000015", - "completion": "0.0000035", - "request": "0", - "image": "0.0006192", - "web_search": "0", - "internal_reasoning": "0", - "input_cache_read": "0.0000000375", - "input_cache_write": "0.0000002333" - }, - "top_provider": { - "context_length": 1048576, - "max_completion_tokens": 65535, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "max_tokens", - "temperature", - "top_p", - "tools", - "tool_choice", - "stop", - "response_format", - "structured_outputs" - ] - }, { "id": "openai/o4-mini-high", "canonical_slug": "openai/o4-mini-high-2025-04-16", @@ -3739,6 +4290,57 @@ "top_logprobs" ] }, + { + "id": "agentica-org/deepcoder-14b-preview", + "canonical_slug": "agentica-org/deepcoder-14b-preview", + "hugging_face_id": "agentica-org/DeepCoder-14B-Preview", + "name": "Agentica: Deepcoder 14B Preview", + "created": 1744555395, + "description": "DeepCoder-14B-Preview is a 14B parameter code generation model fine-tuned from DeepSeek-R1-Distill-Qwen-14B using reinforcement learning with GRPO+ and iterative context lengthening. It is optimized for long-context program synthesis and achieves strong performance across coding benchmarks, including 60.6% on LiveCodeBench v5, competitive with models like o3-Mini", + "context_length": 96000, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Other", + "instruct_type": "deepseek-r1" + }, + "pricing": { + "prompt": "0.000000015", + "completion": "0.000000015", + "request": "0", + "image": "0", + "web_search": "0", + "internal_reasoning": "0" + }, + "top_provider": { + "context_length": 96000, + "max_completion_tokens": null, + "is_moderated": false + }, + "per_request_limits": null, + "supported_parameters": [ + "max_tokens", + "temperature", + "top_p", + "reasoning", + "include_reasoning", + "stop", + "frequency_penalty", + "presence_penalty", + "seed", + "top_k", + "min_p", + "repetition_penalty", + "logprobs", + "logit_bias", + "top_logprobs" + ] + }, { "id": "moonshotai/kimi-vl-a3b-thinking:free", "canonical_slug": "moonshotai/kimi-vl-a3b-thinking", @@ -3889,55 +4491,6 @@ "response_format" ] }, - { - "id": "nvidia/llama-3.3-nemotron-super-49b-v1:free", - "canonical_slug": "nvidia/llama-3.3-nemotron-super-49b-v1", - "hugging_face_id": "nvidia/Llama-3_3-Nemotron-Super-49B-v1", - "name": "NVIDIA: Llama 3.3 Nemotron Super 49B v1 (free)", - "created": 1744119494, - "description": "Llama-3.3-Nemotron-Super-49B-v1 is a large language model (LLM) optimized for advanced reasoning, conversational interactions, retrieval-augmented generation (RAG), and tool-calling tasks. Derived from Meta's Llama-3.3-70B-Instruct, it employs a Neural Architecture Search (NAS) approach, significantly enhancing efficiency and reducing memory requirements. This allows the model to support a context length of up to 128K tokens and fit efficiently on single high-performance GPUs, such as NVIDIA H200.\n\nNote: you must include `detailed thinking on` in the system prompt to enable reasoning. Please see [Usage Recommendations](https://huggingface.co/nvidia/Llama-3_1-Nemotron-Ultra-253B-v1#quick-start-and-usage-recommendations) for more.", - "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": null, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "max_tokens", - "temperature", - "top_p", - "stop", - "frequency_penalty", - "presence_penalty", - "seed", - "top_k", - "min_p", - "repetition_penalty", - "logprobs", - "logit_bias", - "top_logprobs" - ] - }, { "id": "nvidia/llama-3.3-nemotron-super-49b-v1", "canonical_slug": "nvidia/llama-3.3-nemotron-super-49b-v1", @@ -4083,58 +4636,6 @@ "top_logprobs" ] }, - { - "id": "meta-llama/llama-4-maverick:free", - "canonical_slug": "meta-llama/llama-4-maverick-17b-128e-instruct", - "hugging_face_id": "meta-llama/Llama-4-Maverick-17B-128E-Instruct", - "name": "Meta: Llama 4 Maverick (free)", - "created": 1743881822, - "description": "Llama 4 Maverick 17B Instruct (128E) is a high-capacity multimodal language model from Meta, built on a mixture-of-experts (MoE) architecture with 128 experts and 17 billion active parameters per forward pass (400B total). It supports multilingual text and image input, and produces multilingual text and code output across 12 supported languages. Optimized for vision-language tasks, Maverick is instruction-tuned for assistant-like behavior, image reasoning, and general-purpose multimodal interaction.\n\nMaverick features early fusion for native multimodality and a 1 million token context window. It was trained on a curated mixture of public, licensed, and Meta-platform data, covering ~22 trillion tokens, with a knowledge cutoff in August 2024. Released on April 5, 2025 under the Llama 4 Community License, Maverick is suited for research and commercial applications requiring advanced multimodal understanding and high model throughput.", - "context_length": 128000, - "architecture": { - "modality": "text+image->text", - "input_modalities": [ - "text", - "image" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Llama4", - "instruct_type": null - }, - "pricing": { - "prompt": "0", - "completion": "0", - "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", - "top_p", - "structured_outputs", - "response_format", - "stop", - "frequency_penalty", - "presence_penalty", - "seed", - "top_k", - "min_p", - "repetition_penalty", - "logprobs", - "logit_bias", - "top_logprobs" - ] - }, { "id": "meta-llama/llama-4-maverick", "canonical_slug": "meta-llama/llama-4-maverick-17b-128e-instruct", @@ -4181,66 +4682,14 @@ "top_k", "seed", "min_p", + "structured_outputs", "logit_bias", "tools", "tool_choice", - "structured_outputs", "logprobs", "top_logprobs" ] }, - { - "id": "meta-llama/llama-4-scout:free", - "canonical_slug": "meta-llama/llama-4-scout-17b-16e-instruct", - "hugging_face_id": "meta-llama/Llama-4-Scout-17B-16E-Instruct", - "name": "Meta: Llama 4 Scout (free)", - "created": 1743881519, - "description": "Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input (text and image) and multilingual output (text and code) across 12 supported languages. Designed for assistant-style interaction and visual reasoning, Scout uses 16 experts per forward pass and features a context length of 10 million tokens, with a training corpus of ~40 trillion tokens.\n\nBuilt for high efficiency and local or commercial deployment, Llama 4 Scout incorporates early fusion for seamless modality integration. It is instruction-tuned for use in multilingual chat, captioning, and image understanding tasks. Released under the Llama 4 Community License, it was last trained on data up to August 2024 and launched publicly on April 5, 2025.", - "context_length": 64000, - "architecture": { - "modality": "text+image->text", - "input_modalities": [ - "text", - "image" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Llama4", - "instruct_type": null - }, - "pricing": { - "prompt": "0", - "completion": "0", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 64000, - "max_completion_tokens": null, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "max_tokens", - "temperature", - "top_p", - "structured_outputs", - "response_format", - "stop", - "frequency_penalty", - "presence_penalty", - "seed", - "top_k", - "min_p", - "repetition_penalty", - "logprobs", - "logit_bias", - "top_logprobs" - ] - }, { "id": "meta-llama/llama-4-scout", "canonical_slug": "meta-llama/llama-4-scout-17b-16e-instruct", @@ -4279,68 +4728,20 @@ "max_tokens", "temperature", "top_p", + "structured_outputs", + "response_format", "stop", "frequency_penalty", "presence_penalty", "seed", - "response_format", - "tools", - "tool_choice", - "structured_outputs", - "repetition_penalty", - "top_k", - "top_logprobs", - "logprobs", - "logit_bias", - "min_p" - ] - }, - { - "id": "all-hands/openhands-lm-32b-v0.1", - "canonical_slug": "all-hands/openhands-lm-32b-v0.1", - "hugging_face_id": "all-hands/openhands-lm-32b-v0.1", - "name": "OpenHands LM 32B V0.1", - "created": 1743613013, - "description": "OpenHands LM v0.1 is a 32B open-source coding model fine-tuned from Qwen2.5-Coder-32B-Instruct using reinforcement learning techniques outlined in SWE-Gym. It is optimized for autonomous software development agents and achieves strong performance on SWE-Bench Verified, with a 37.2% resolve rate. The model supports a 128K token context window, making it well-suited for long-horizon code reasoning and large codebase tasks.\n\nOpenHands LM is designed for local deployment and runs on consumer-grade GPUs such as a single 3090. It enables fully offline agent workflows without dependency on proprietary APIs. This release is intended as a research preview, and future updates aim to improve generalizability, reduce repetition, and offer smaller variants.", - "context_length": 16384, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Other", - "instruct_type": null - }, - "pricing": { - "prompt": "0.0000026", - "completion": "0.0000034", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 16384, - "max_completion_tokens": 4096, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "max_tokens", - "temperature", - "top_p", - "tools", - "tool_choice", - "stop", - "frequency_penalty", - "presence_penalty", - "repetition_penalty", "top_k", "min_p", - "seed" + "repetition_penalty", + "tools", + "tool_choice", + "top_logprobs", + "logprobs", + "logit_bias" ] }, { @@ -4558,8 +4959,8 @@ "instruct_type": null }, "pricing": { - "prompt": "0.0000009", - "completion": "0.0000009", + "prompt": "0.0000002", + "completion": "0.0000006", "request": "0", "image": "0", "web_search": "0", @@ -4578,9 +4979,11 @@ "stop", "frequency_penalty", "presence_penalty", - "top_k", "repetition_penalty", "response_format", + "top_k", + "seed", + "min_p", "structured_outputs", "logit_bias", "logprobs", @@ -4594,7 +4997,7 @@ "name": "DeepSeek: DeepSeek V3 0324 (free)", "created": 1742824755, "description": "DeepSeek V3, a 685B-parameter, mixture-of-experts model, is the latest iteration of the flagship chat model family from the DeepSeek team.\n\nIt succeeds the [DeepSeek V3](/deepseek/deepseek-chat-v3) model and performs really well on a variety of tasks.", - "context_length": 16384, + "context_length": 32768, "architecture": { "modality": "text->text", "input_modalities": [ @@ -4615,7 +5018,7 @@ "internal_reasoning": "0" }, "top_provider": { - "context_length": 16384, + "context_length": 32768, "max_completion_tokens": 16384, "is_moderated": false }, @@ -4635,8 +5038,7 @@ "repetition_penalty", "logprobs", "logit_bias", - "top_logprobs", - "top_a" + "top_logprobs" ] }, { @@ -4659,8 +5061,8 @@ "instruct_type": null }, "pricing": { - "prompt": "0.00000028", - "completion": "0.00000088", + "prompt": "0.00000025", + "completion": "0.00000085", "request": "0", "image": "0", "web_search": "0", @@ -4668,7 +5070,7 @@ }, "top_provider": { "context_length": 163840, - "max_completion_tokens": null, + "max_completion_tokens": 163840, "is_moderated": false }, "per_request_limits": null, @@ -4786,7 +5188,7 @@ "name": "Mistral: Mistral Small 3.1 24B (free)", "created": 1742238937, "description": "Mistral Small 3.1 24B Instruct is an upgraded variant of Mistral Small 3 (2501), featuring 24 billion parameters with advanced multimodal capabilities. It provides state-of-the-art performance in text-based reasoning and vision tasks, including image analysis, programming, mathematical reasoning, and multilingual support across dozens of languages. Equipped with an extensive 128k token context window and optimized for efficient local inference, it supports use cases such as conversational agents, function calling, long-document comprehension, and privacy-sensitive deployments. The updated version is [Mistral Small 3.2](mistralai/mistral-small-3.2-24b-instruct)", - "context_length": 96000, + "context_length": 128000, "architecture": { "modality": "text+image->text", "input_modalities": [ @@ -4808,8 +5210,8 @@ "internal_reasoning": "0" }, "top_provider": { - "context_length": 96000, - "max_completion_tokens": 96000, + "context_length": 128000, + "max_completion_tokens": null, "is_moderated": false }, "per_request_limits": null, @@ -4819,11 +5221,13 @@ "top_p", "tools", "tool_choice", + "structured_outputs", + "response_format", "stop", "frequency_penalty", "presence_penalty", - "seed", "top_k", + "seed", "min_p", "repetition_penalty", "logprobs", @@ -5119,7 +5523,7 @@ "name": "Google: Gemma 3 12B", "created": 1741902625, "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 12B is the second largest in the family of Gemma 3 models after [Gemma 3 27B](google/gemma-3-27b-it)", - "context_length": 131072, + "context_length": 96000, "architecture": { "modality": "text+image->text", "input_modalities": [ @@ -5133,16 +5537,16 @@ "instruct_type": "gemma" }, "pricing": { - "prompt": "0.00000005", - "completion": "0.0000001", + "prompt": "0.00000003", + "completion": "0.00000003", "request": "0", "image": "0", "web_search": "0", "internal_reasoning": "0" }, "top_provider": { - "context_length": 131072, - "max_completion_tokens": null, + "context_length": 96000, + "max_completion_tokens": 8192, "is_moderated": false }, "per_request_limits": null, @@ -5153,11 +5557,14 @@ "stop", "frequency_penalty", "presence_penalty", - "repetition_penalty", - "response_format", - "top_k", "seed", - "min_p" + "top_k", + "min_p", + "repetition_penalty", + "logprobs", + "logit_bias", + "top_logprobs", + "response_format" ] }, { @@ -5337,6 +5744,57 @@ "top_logprobs" ] }, + { + "id": "rekaai/reka-flash-3", + "canonical_slug": "rekaai/reka-flash-3", + "hugging_face_id": "RekaAI/reka-flash-3", + "name": "Reka: Flash 3", + "created": 1741812813, + "description": "Reka Flash 3 is a general-purpose, instruction-tuned large language model with 21 billion parameters, developed by Reka. It excels at general chat, coding tasks, instruction-following, and function calling. Featuring a 32K context length and optimized through reinforcement learning (RLOO), it provides competitive performance comparable to proprietary models within a smaller parameter footprint. Ideal for low-latency, local, or on-device deployments, Reka Flash 3 is compact, supports efficient quantization (down to 11GB at 4-bit precision), and employs explicit reasoning tags (\"\") to indicate its internal thought process.\n\nReka Flash 3 is primarily an English model with limited multilingual understanding capabilities. The model weights are released under the Apache 2.0 license.", + "context_length": 32768, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Other", + "instruct_type": null + }, + "pricing": { + "prompt": "0.000000013", + "completion": "0.000000013", + "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": [ + "max_tokens", + "temperature", + "top_p", + "reasoning", + "include_reasoning", + "stop", + "frequency_penalty", + "presence_penalty", + "seed", + "top_k", + "min_p", + "repetition_penalty", + "logprobs", + "logit_bias", + "top_logprobs" + ] + }, { "id": "google/gemma-3-27b-it:free", "canonical_slug": "google/gemma-3-27b-it", @@ -5460,7 +5918,7 @@ "instruct_type": null }, "pricing": { - "prompt": "0.0000008", + "prompt": "0.0000005", "completion": "0.000001", "request": "0", "image": "0", @@ -5477,9 +5935,12 @@ "max_tokens", "temperature", "top_p", - "presence_penalty", "frequency_penalty", + "min_p", + "presence_penalty", "repetition_penalty", + "seed", + "stop", "top_k" ] }, @@ -5503,8 +5964,8 @@ "instruct_type": null }, "pricing": { - "prompt": "0.0000005", - "completion": "0.0000008", + "prompt": "0.0000004", + "completion": "0.0000007", "request": "0", "image": "0", "web_search": "0", @@ -5512,7 +5973,7 @@ }, "top_provider": { "context_length": 32768, - "max_completion_tokens": 32768, + "max_completion_tokens": null, "is_moderated": false }, "per_request_limits": null, @@ -5520,9 +5981,14 @@ "max_tokens", "temperature", "top_p", - "presence_penalty", + "stop", "frequency_penalty", + "presence_penalty", + "response_format", + "structured_outputs", + "min_p", "repetition_penalty", + "seed", "top_k" ] }, @@ -5715,7 +6181,7 @@ "name": "Qwen: QwQ 32B (free)", "created": 1741208814, "description": "QwQ is the reasoning model of the Qwen series. Compared with conventional instruction-tuned models, QwQ, which is capable of thinking and reasoning, can achieve significantly enhanced performance in downstream tasks, especially hard problems. QwQ-32B is the medium-sized reasoning model, which is capable of achieving competitive performance against state-of-the-art reasoning models, e.g., DeepSeek-R1, o1-mini.", - "context_length": 131072, + "context_length": 32768, "architecture": { "modality": "text->text", "input_modalities": [ @@ -5736,22 +6202,24 @@ "internal_reasoning": "0" }, "top_provider": { - "context_length": 131072, + "context_length": 32768, "max_completion_tokens": null, - "is_moderated": true + "is_moderated": false }, "per_request_limits": null, "supported_parameters": [ "max_tokens", "temperature", "top_p", - "reasoning", - "include_reasoning", + "structured_outputs", + "response_format", "stop", "frequency_penalty", "presence_penalty", - "seed", "top_k", + "reasoning", + "include_reasoning", + "seed", "min_p", "repetition_penalty", "logprobs", @@ -5808,8 +6276,7 @@ "response_format", "logprobs", "top_logprobs", - "seed", - "structured_outputs" + "seed" ] }, { @@ -5861,58 +6328,6 @@ "top_logprobs" ] }, - { - "id": "openai/gpt-4.5-preview", - "canonical_slug": "openai/gpt-4.5-preview-2025-02-27", - "hugging_face_id": "", - "name": "OpenAI: GPT-4.5 (Preview)", - "created": 1740687810, - "description": "GPT-4.5 (Preview) is a research preview of OpenAI’s latest language model, designed to advance capabilities in reasoning, creativity, and multi-turn conversation. It builds on previous iterations with improvements in world knowledge, contextual coherence, and the ability to follow user intent more effectively.\n\nThe model demonstrates enhanced performance in tasks that require open-ended thinking, problem-solving, and communication. Early testing suggests it is better at generating nuanced responses, maintaining long-context coherence, and reducing hallucinations compared to earlier versions.\n\nThis research preview is intended to help evaluate GPT-4.5’s strengths and limitations in real-world use cases as OpenAI continues to refine and develop future models. Read more at the [blog post here.](https://openai.com/index/introducing-gpt-4-5/)", - "context_length": 128000, - "architecture": { - "modality": "text+image->text", - "input_modalities": [ - "text", - "image" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "GPT", - "instruct_type": null - }, - "pricing": { - "prompt": "0.000075", - "completion": "0.00015", - "request": "0", - "image": "0.108375", - "web_search": "0", - "internal_reasoning": "0", - "input_cache_read": "0.0000375" - }, - "top_provider": { - "context_length": 128000, - "max_completion_tokens": 16384, - "is_moderated": true - }, - "per_request_limits": null, - "supported_parameters": [ - "max_tokens", - "temperature", - "top_p", - "tools", - "tool_choice", - "stop", - "frequency_penalty", - "presence_penalty", - "seed", - "logit_bias", - "logprobs", - "top_logprobs", - "response_format", - "structured_outputs" - ] - }, { "id": "google/gemini-2.0-flash-lite-001", "canonical_slug": "google/gemini-2.0-flash-lite-001", @@ -6249,6 +6664,57 @@ "top_logprobs" ] }, + { + "id": "cognitivecomputations/dolphin3.0-r1-mistral-24b", + "canonical_slug": "cognitivecomputations/dolphin3.0-r1-mistral-24b", + "hugging_face_id": "cognitivecomputations/Dolphin3.0-R1-Mistral-24B", + "name": "Dolphin3.0 R1 Mistral 24B", + "created": 1739462498, + "description": "Dolphin 3.0 R1 is the next generation of the Dolphin series of instruct-tuned models. Designed to be the ultimate general purpose local model, enabling coding, math, agentic, function calling, and general use cases.\n\nThe R1 version has been trained for 3 epochs to reason using 800k reasoning traces from the Dolphin-R1 dataset.\n\nDolphin aims to be a general purpose reasoning instruct model, similar to the models behind ChatGPT, Claude, Gemini.\n\nPart of the [Dolphin 3.0 Collection](https://huggingface.co/collections/cognitivecomputations/dolphin-30-677ab47f73d7ff66743979a3) Curated and trained by [Eric Hartford](https://huggingface.co/ehartford), [Ben Gitter](https://huggingface.co/bigstorm), [BlouseJury](https://huggingface.co/BlouseJury) and [Cognitive Computations](https://huggingface.co/cognitivecomputations)", + "context_length": 32768, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Other", + "instruct_type": "deepseek-r1" + }, + "pricing": { + "prompt": "0.000000013", + "completion": "0.000000013", + "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": [ + "max_tokens", + "temperature", + "top_p", + "reasoning", + "include_reasoning", + "stop", + "frequency_penalty", + "presence_penalty", + "seed", + "top_k", + "min_p", + "repetition_penalty", + "logprobs", + "logit_bias", + "top_logprobs" + ] + }, { "id": "cognitivecomputations/dolphin3.0-mistral-24b:free", "canonical_slug": "cognitivecomputations/dolphin3.0-mistral-24b", @@ -6340,13 +6806,12 @@ "presence_penalty", "top_k", "repetition_penalty", - "response_format", - "structured_outputs", "logit_bias", - "logprobs", - "top_logprobs", "min_p", - "seed" + "response_format", + "seed", + "logprobs", + "top_logprobs" ] }, { @@ -6748,7 +7213,7 @@ "name": "Qwen: Qwen2.5 VL 72B Instruct (free)", "created": 1738410311, "description": "Qwen2.5-VL is proficient in recognizing common objects such as flowers, birds, fish, and insects. It is also highly capable of analyzing texts, charts, icons, graphics, and layouts within images.", - "context_length": 131072, + "context_length": 32768, "architecture": { "modality": "text+image->text", "input_modalities": [ @@ -6770,8 +7235,8 @@ "internal_reasoning": "0" }, "top_provider": { - "context_length": 131072, - "max_completion_tokens": 2048, + "context_length": 32768, + "max_completion_tokens": null, "is_moderated": false }, "per_request_limits": null, @@ -6779,9 +7244,13 @@ "max_tokens", "temperature", "top_p", - "seed", + "structured_outputs", "response_format", - "presence_penalty" + "stop", + "frequency_penalty", + "presence_penalty", + "top_k", + "seed" ] }, { @@ -7086,8 +7555,8 @@ "instruct_type": null }, "pricing": { - "prompt": "0.00000005", - "completion": "0.00000008", + "prompt": "0.00000003", + "completion": "0.00000003", "request": "0", "image": "0", "web_search": "0", @@ -7095,7 +7564,7 @@ }, "top_provider": { "context_length": 32768, - "max_completion_tokens": 32768, + "max_completion_tokens": null, "is_moderated": false }, "per_request_limits": null, @@ -7527,8 +7996,8 @@ "instruct_type": "deepseek-r1" }, "pricing": { - "prompt": "0.0000001", - "completion": "0.0000004", + "prompt": "0.00000005", + "completion": "0.00000005", "request": "0", "image": "0", "web_search": "0", @@ -7536,7 +8005,7 @@ }, "top_provider": { "context_length": 131072, - "max_completion_tokens": 16384, + "max_completion_tokens": null, "is_moderated": false }, "per_request_limits": null, @@ -7547,15 +8016,15 @@ "reasoning", "include_reasoning", "seed", - "top_k", "stop", "frequency_penalty", "presence_penalty", - "logit_bias", - "logprobs", - "top_logprobs", + "top_k", "min_p", "repetition_penalty", + "logprobs", + "logit_bias", + "top_logprobs", "tools", "tool_choice", "response_format", @@ -7599,15 +8068,7 @@ "max_tokens", "reasoning", "include_reasoning", - "temperature", - "top_p", - "stop", - "frequency_penalty", - "presence_penalty", - "seed", - "top_k", - "top_a", - "logprobs" + "temperature" ] }, { @@ -7617,7 +8078,7 @@ "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": 128000, + "context_length": 163840, "architecture": { "modality": "text->text", "input_modalities": [ @@ -7630,16 +8091,16 @@ "instruct_type": "deepseek-r1" }, "pricing": { - "prompt": "0.00000045", - "completion": "0.00000215", + "prompt": "0.0000004", + "completion": "0.000002", "request": "0", "image": "0", "web_search": "0", "internal_reasoning": "0" }, "top_provider": { - "context_length": 128000, - "max_completion_tokens": 32768, + "context_length": 163840, + "max_completion_tokens": 163840, "is_moderated": false }, "per_request_limits": null, @@ -7659,8 +8120,8 @@ "top_logprobs", "response_format", "structured_outputs", - "logprobs", "repetition_penalty", + "logprobs", "tools", "tool_choice" ] @@ -7848,8 +8309,7 @@ "repetition_penalty", "logprobs", "logit_bias", - "top_logprobs", - "top_a" + "top_logprobs" ] }, { @@ -7872,8 +8332,8 @@ "instruct_type": null }, "pricing": { - "prompt": "0.00000038", - "completion": "0.00000089", + "prompt": "0.0000003", + "completion": "0.00000085", "request": "0", "image": "0", "web_search": "0", @@ -8223,6 +8683,8 @@ "max_tokens", "temperature", "top_p", + "tools", + "tool_choice", "stop" ] }, @@ -8233,7 +8695,7 @@ "name": "Meta: Llama 3.3 70B Instruct (free)", "created": 1733506137, "description": "The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model is optimized for multilingual dialogue use cases and outperforms many of the available open source and closed chat models on common industry benchmarks.\n\nSupported languages: English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai.\n\n[Model Card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_3/MODEL_CARD.md)", - "context_length": 131072, + "context_length": 65536, "architecture": { "modality": "text->text", "input_modalities": [ @@ -8254,8 +8716,8 @@ "internal_reasoning": "0" }, "top_provider": { - "context_length": 131072, - "max_completion_tokens": 2048, + "context_length": 65536, + "max_completion_tokens": null, "is_moderated": false }, "per_request_limits": null, @@ -8263,6 +8725,8 @@ "max_tokens", "temperature", "top_p", + "tools", + "tool_choice", "stop", "frequency_penalty", "presence_penalty", @@ -8280,7 +8744,7 @@ "name": "Meta: Llama 3.3 70B Instruct", "created": 1733506137, "description": "The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model is optimized for multilingual dialogue use cases and outperforms many of the available open source and closed chat models on common industry benchmarks.\n\nSupported languages: English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai.\n\n[Model Card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_3/MODEL_CARD.md)", - "context_length": 131000, + "context_length": 131072, "architecture": { "modality": "text->text", "input_modalities": [ @@ -8301,8 +8765,8 @@ "internal_reasoning": "0" }, "top_provider": { - "context_length": 131000, - "max_completion_tokens": 131000, + "context_length": 131072, + "max_completion_tokens": 16384, "is_moderated": false }, "per_request_limits": null, @@ -8320,10 +8784,10 @@ "top_k", "seed", "min_p", + "structured_outputs", "logit_bias", "logprobs", - "top_logprobs", - "structured_outputs" + "top_logprobs" ] }, { @@ -8878,8 +9342,8 @@ "stop", "frequency_penalty", "presence_penalty", - "seed", "top_k", + "seed", "min_p", "repetition_penalty", "logprobs", @@ -8984,52 +9448,6 @@ "seed" ] }, - { - "id": "eva-unit-01/eva-qwen-2.5-32b", - "canonical_slug": "eva-unit-01/eva-qwen-2.5-32b", - "hugging_face_id": "EVA-UNIT-01/EVA-Qwen2.5-32B-v0.2", - "name": "EVA Qwen2.5 32B", - "created": 1731104847, - "description": "EVA Qwen2.5 32B is a roleplaying/storywriting specialist model. It's a full-parameter finetune of Qwen2.5-32B on mixture of synthetic and natural data.\n\nIt uses Celeste 70B 0.1 data mixture, greatly expanding it to improve versatility, creativity and \"flavor\" of the resulting model.", - "context_length": 16384, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Qwen", - "instruct_type": "chatml" - }, - "pricing": { - "prompt": "0.0000026", - "completion": "0.0000034", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 16384, - "max_completion_tokens": 4096, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "max_tokens", - "temperature", - "top_p", - "stop", - "frequency_penalty", - "presence_penalty", - "repetition_penalty", - "top_k", - "min_p", - "seed" - ] - }, { "id": "thedrummer/unslopnemo-12b", "canonical_slug": "thedrummer/unslopnemo-12b", @@ -9266,54 +9684,6 @@ "stop" ] }, - { - "id": "neversleep/llama-3.1-lumimaid-70b", - "canonical_slug": "neversleep/llama-3.1-lumimaid-70b", - "hugging_face_id": "NeverSleep/Lumimaid-v0.2-70B", - "name": "NeverSleep: Lumimaid v0.2 70B", - "created": 1729555200, - "description": "Lumimaid v0.2 70B is a finetune of [Llama 3.1 70B](/meta-llama/llama-3.1-70b-instruct) with a \"HUGE step up dataset wise\" compared to Lumimaid v0.1. Sloppy chats output were purged.\n\nUsage 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": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Llama3", - "instruct_type": "llama3" - }, - "pricing": { - "prompt": "0.0000025", - "completion": "0.000003", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 16384, - "max_completion_tokens": 2048, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "max_tokens", - "temperature", - "top_p", - "stop", - "frequency_penalty", - "presence_penalty", - "repetition_penalty", - "logit_bias", - "top_k", - "min_p", - "seed", - "top_a" - ] - }, { "id": "anthracite-org/magnum-v4-72b", "canonical_slug": "anthracite-org/magnum-v4-72b", @@ -9454,53 +9824,6 @@ "stop" ] }, - { - "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": 128000, - "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": 128000, - "max_completion_tokens": null, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "max_tokens", - "temperature", - "top_p", - "tools", - "tool_choice", - "stop", - "frequency_penalty", - "presence_penalty", - "response_format", - "structured_outputs", - "seed" - ] - }, { "id": "mistralai/ministral-3b", "canonical_slug": "mistralai/ministral-3b", @@ -9548,6 +9871,53 @@ "seed" ] }, + { + "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": 128000, + "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": 128000, + "max_completion_tokens": null, + "is_moderated": false + }, + "per_request_limits": null, + "supported_parameters": [ + "max_tokens", + "temperature", + "top_p", + "tools", + "tool_choice", + "stop", + "frequency_penalty", + "presence_penalty", + "response_format", + "structured_outputs", + "seed" + ] + }, { "id": "qwen/qwen-2.5-7b-instruct", "canonical_slug": "qwen/qwen-2.5-7b-instruct", @@ -9768,11 +10138,11 @@ "max_tokens", "temperature", "top_p", + "tools", + "tool_choice", "stop", "frequency_penalty", "presence_penalty", - "tools", - "tool_choice", "seed", "response_format", "structured_outputs" @@ -9820,58 +10190,14 @@ "presence_penalty", "response_format", "structured_outputs", - "repetition_penalty", - "top_k", - "min_p", - "seed", - "logit_bias" - ] - }, - { - "id": "anthracite-org/magnum-v2-72b", - "canonical_slug": "anthracite-org/magnum-v2-72b", - "hugging_face_id": "anthracite-org/magnum-v2-72b", - "name": "Magnum v2 72B", - "created": 1727654400, - "description": "From the maker of [Goliath](https://openrouter.ai/models/alpindale/goliath-120b), Magnum 72B is the seventh in a family of models designed to achieve the prose quality of the Claude 3 models, notably Opus & Sonnet.\n\nThe model is based on [Qwen2 72B](https://openrouter.ai/models/qwen/qwen-2-72b-instruct) and trained with 55 million tokens of highly curated roleplay (RP) data.", - "context_length": 32768, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Qwen", - "instruct_type": "chatml" - }, - "pricing": { - "prompt": "0.000003", - "completion": "0.000003", - "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": [ - "max_tokens", - "temperature", - "top_p", - "stop", - "frequency_penalty", - "presence_penalty", - "repetition_penalty", + "tools", + "tool_choice", "logit_bias", + "logprobs", + "seed", + "repetition_penalty", "top_k", - "min_p", - "seed" + "min_p" ] }, { @@ -9924,6 +10250,96 @@ "response_format" ] }, + { + "id": "anthracite-org/magnum-v2-72b", + "canonical_slug": "anthracite-org/magnum-v2-72b", + "hugging_face_id": "anthracite-org/magnum-v2-72b", + "name": "Magnum v2 72B", + "created": 1727654400, + "description": "From the maker of [Goliath](https://openrouter.ai/models/alpindale/goliath-120b), Magnum 72B is the seventh in a family of models designed to achieve the prose quality of the Claude 3 models, notably Opus & Sonnet.\n\nThe model is based on [Qwen2 72B](https://openrouter.ai/models/qwen/qwen-2-72b-instruct) and trained with 55 million tokens of highly curated roleplay (RP) data.", + "context_length": 32768, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Qwen", + "instruct_type": "chatml" + }, + "pricing": { + "prompt": "0.000003", + "completion": "0.000003", + "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": [ + "max_tokens", + "temperature", + "top_p", + "stop", + "frequency_penalty", + "presence_penalty", + "repetition_penalty", + "logit_bias", + "top_k", + "min_p", + "seed" + ] + }, + { + "id": "meta-llama/llama-3.2-3b-instruct:free", + "canonical_slug": "meta-llama/llama-3.2-3b-instruct", + "hugging_face_id": "meta-llama/Llama-3.2-3B-Instruct", + "name": "Meta: Llama 3.2 3B Instruct (free)", + "created": 1727222400, + "description": "Llama 3.2 3B is a 3-billion-parameter multilingual large language model, optimized for advanced natural language processing tasks like dialogue generation, reasoning, and summarization. Designed with the latest transformer architecture, it supports eight languages, including English, Spanish, and Hindi, and is adaptable for additional languages.\n\nTrained on 9 trillion tokens, the Llama 3.2 3B model excels in instruction-following, complex reasoning, and tool use. Its balanced performance makes it ideal for applications needing accuracy and efficiency in text generation across multilingual settings.\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": 131072, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Llama3", + "instruct_type": "llama3" + }, + "pricing": { + "prompt": "0", + "completion": "0", + "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": [ + "max_tokens", + "temperature", + "top_p", + "stop", + "frequency_penalty", + "presence_penalty", + "top_k" + ] + }, { "id": "meta-llama/llama-3.2-3b-instruct", "canonical_slug": "meta-llama/llama-3.2-3b-instruct", @@ -10025,55 +10441,6 @@ "top_logprobs" ] }, - { - "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": 131072, - "architecture": { - "modality": "text+image->text", - "input_modalities": [ - "text", - "image" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Llama3", - "instruct_type": "llama3" - }, - "pricing": { - "prompt": "0.0000012", - "completion": "0.0000012", - "request": "0", - "image": "0.001734", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 131072, - "max_completion_tokens": 2048, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "max_tokens", - "temperature", - "top_p", - "stop", - "frequency_penalty", - "presence_penalty", - "top_k", - "repetition_penalty", - "logit_bias", - "min_p", - "response_format", - "seed" - ] - }, { "id": "meta-llama/llama-3.2-11b-vision-instruct:free", "canonical_slug": "meta-llama/llama-3.2-11b-vision-instruct", @@ -10175,6 +10542,55 @@ "logprobs" ] }, + { + "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": 131072, + "architecture": { + "modality": "text+image->text", + "input_modalities": [ + "text", + "image" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Llama3", + "instruct_type": "llama3" + }, + "pricing": { + "prompt": "0.0000012", + "completion": "0.0000012", + "request": "0", + "image": "0.001734", + "web_search": "0", + "internal_reasoning": "0" + }, + "top_provider": { + "context_length": 131072, + "max_completion_tokens": 2048, + "is_moderated": false + }, + "per_request_limits": null, + "supported_parameters": [ + "max_tokens", + "temperature", + "top_p", + "stop", + "frequency_penalty", + "presence_penalty", + "top_k", + "repetition_penalty", + "logit_bias", + "min_p", + "response_format", + "seed" + ] + }, { "id": "qwen/qwen-2.5-72b-instruct:free", "canonical_slug": "qwen/qwen-2.5-72b-instruct", @@ -10261,19 +10677,18 @@ "max_tokens", "temperature", "top_p", - "tools", - "tool_choice", "stop", "frequency_penalty", "presence_penalty", + "seed", "top_k", - "repetition_penalty", - "response_format", - "structured_outputs", "logit_bias", "logprobs", "top_logprobs", - "seed", + "tools", + "tool_choice", + "repetition_penalty", + "response_format", "min_p" ] }, @@ -10297,8 +10712,8 @@ "instruct_type": "llama3" }, "pricing": { - "prompt": "0.0000002", - "completion": "0.00000125", + "prompt": "0.00000018", + "completion": "0.000001", "request": "0", "image": "0", "web_search": "0", @@ -10306,7 +10721,7 @@ }, "top_provider": { "context_length": 32768, - "max_completion_tokens": 2048, + "max_completion_tokens": null, "is_moderated": false }, "per_request_limits": null, @@ -10317,6 +10732,8 @@ "stop", "frequency_penalty", "presence_penalty", + "response_format", + "structured_outputs", "repetition_penalty", "top_k", "min_p", @@ -10364,6 +10781,45 @@ "max_tokens" ] }, + { + "id": "openai/o1-mini-2024-09-12", + "canonical_slug": "openai/o1-mini-2024-09-12", + "hugging_face_id": null, + "name": "OpenAI: o1-mini (2024-09-12)", + "created": 1726099200, + "description": "The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding.\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\nNote: This model is currently experimental and not suitable for production use-cases, and may be heavily rate-limited.", + "context_length": 128000, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "GPT", + "instruct_type": null + }, + "pricing": { + "prompt": "0.0000011", + "completion": "0.0000044", + "request": "0", + "image": "0", + "web_search": "0", + "internal_reasoning": "0", + "input_cache_read": "0.00000055" + }, + "top_provider": { + "context_length": 128000, + "max_completion_tokens": 65536, + "is_moderated": true + }, + "per_request_limits": null, + "supported_parameters": [ + "seed", + "max_tokens" + ] + }, { "id": "openai/o1-preview-2024-09-12", "canonical_slug": "openai/o1-preview-2024-09-12", @@ -10442,45 +10898,6 @@ "max_tokens" ] }, - { - "id": "openai/o1-mini-2024-09-12", - "canonical_slug": "openai/o1-mini-2024-09-12", - "hugging_face_id": null, - "name": "OpenAI: o1-mini (2024-09-12)", - "created": 1726099200, - "description": "The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding.\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\nNote: This model is currently experimental and not suitable for production use-cases, and may be heavily rate-limited.", - "context_length": 128000, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "GPT", - "instruct_type": null - }, - "pricing": { - "prompt": "0.0000011", - "completion": "0.0000044", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0", - "input_cache_read": "0.00000055" - }, - "top_provider": { - "context_length": 128000, - "max_completion_tokens": 65536, - "is_moderated": true - }, - "per_request_limits": null, - "supported_parameters": [ - "seed", - "max_tokens" - ] - }, { "id": "mistralai/pixtral-12b", "canonical_slug": "mistralai/pixtral-12b", @@ -10920,6 +11337,52 @@ "structured_outputs" ] }, + { + "id": "aetherwiing/mn-starcannon-12b", + "canonical_slug": "aetherwiing/mn-starcannon-12b", + "hugging_face_id": "aetherwiing/MN-12B-Starcannon-v2", + "name": "Aetherwiing: Starcannon 12B", + "created": 1723507200, + "description": "Starcannon 12B v2 is a creative roleplay and story writing model, based on Mistral Nemo, using [nothingiisreal/mn-celeste-12b](/nothingiisreal/mn-celeste-12b) as a base, with [intervitens/mini-magnum-12b-v1.1](https://huggingface.co/intervitens/mini-magnum-12b-v1.1) merged in using the [TIES](https://arxiv.org/abs/2306.01708) method.\n\nAlthough more similar to Magnum overall, the model remains very creative, with a pleasant writing style. It is recommended for people wanting more variety than Magnum, and yet more verbose prose than Celeste.", + "context_length": 16384, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Mistral", + "instruct_type": "chatml" + }, + "pricing": { + "prompt": "0.0000008", + "completion": "0.0000012", + "request": "0", + "image": "0", + "web_search": "0", + "internal_reasoning": "0" + }, + "top_provider": { + "context_length": 16384, + "max_completion_tokens": 4096, + "is_moderated": false + }, + "per_request_limits": null, + "supported_parameters": [ + "max_tokens", + "temperature", + "top_p", + "stop", + "frequency_penalty", + "presence_penalty", + "repetition_penalty", + "top_k", + "min_p", + "seed" + ] + }, { "id": "sao10k/l3-lunaris-8b", "canonical_slug": "sao10k/l3-lunaris-8b", @@ -10968,52 +11431,6 @@ "response_format" ] }, - { - "id": "aetherwiing/mn-starcannon-12b", - "canonical_slug": "aetherwiing/mn-starcannon-12b", - "hugging_face_id": "aetherwiing/MN-12B-Starcannon-v2", - "name": "Aetherwiing: Starcannon 12B", - "created": 1723507200, - "description": "Starcannon 12B v2 is a creative roleplay and story writing model, based on Mistral Nemo, using [nothingiisreal/mn-celeste-12b](/nothingiisreal/mn-celeste-12b) as a base, with [intervitens/mini-magnum-12b-v1.1](https://huggingface.co/intervitens/mini-magnum-12b-v1.1) merged in using the [TIES](https://arxiv.org/abs/2306.01708) method.\n\nAlthough more similar to Magnum overall, the model remains very creative, with a pleasant writing style. It is recommended for people wanting more variety than Magnum, and yet more verbose prose than Celeste.", - "context_length": 16384, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Mistral", - "instruct_type": "chatml" - }, - "pricing": { - "prompt": "0.0000008", - "completion": "0.0000012", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 16384, - "max_completion_tokens": 4096, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "max_tokens", - "temperature", - "top_p", - "stop", - "frequency_penalty", - "presence_penalty", - "repetition_penalty", - "top_k", - "min_p", - "seed" - ] - }, { "id": "openai/gpt-4o-2024-08-06", "canonical_slug": "openai/gpt-4o-2024-08-06", @@ -11163,90 +11580,6 @@ "seed" ] }, - { - "id": "perplexity/llama-3.1-sonar-small-128k-online", - "canonical_slug": "perplexity/llama-3.1-sonar-small-128k-online", - "hugging_face_id": null, - "name": "Perplexity: Llama 3.1 Sonar 8B Online", - "created": 1722470400, - "description": "Llama 3.1 Sonar is Perplexity's latest model family. It surpasses their earlier Sonar models in cost-efficiency, speed, and performance.\n\nThis is the online version of the [offline chat model](/models/perplexity/llama-3.1-sonar-small-128k-chat). It is focused on delivering helpful, up-to-date, and factual responses. #online", - "context_length": 127072, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Llama3", - "instruct_type": null - }, - "pricing": { - "prompt": "0.0000002", - "completion": "0.0000002", - "request": "0.005", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 127072, - "max_completion_tokens": null, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "max_tokens", - "temperature", - "top_p", - "top_k", - "frequency_penalty", - "presence_penalty" - ] - }, - { - "id": "perplexity/llama-3.1-sonar-large-128k-online", - "canonical_slug": "perplexity/llama-3.1-sonar-large-128k-online", - "hugging_face_id": null, - "name": "Perplexity: Llama 3.1 Sonar 70B Online", - "created": 1722470400, - "description": "Llama 3.1 Sonar is Perplexity's latest model family. It surpasses their earlier Sonar models in cost-efficiency, speed, and performance.\n\nThis is the online version of the [offline chat model](/models/perplexity/llama-3.1-sonar-large-128k-chat). It is focused on delivering helpful, up-to-date, and factual responses. #online", - "context_length": 127072, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Llama3", - "instruct_type": null - }, - "pricing": { - "prompt": "0.000001", - "completion": "0.000001", - "request": "0.005", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 127072, - "max_completion_tokens": null, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "max_tokens", - "temperature", - "top_p", - "top_k", - "frequency_penalty", - "presence_penalty" - ] - }, { "id": "meta-llama/llama-3.1-8b-instruct", "canonical_slug": "meta-llama/llama-3.1-8b-instruct", @@ -11300,59 +11633,6 @@ "structured_outputs" ] }, - { - "id": "meta-llama/llama-3.1-405b-instruct", - "canonical_slug": "meta-llama/llama-3.1-405b-instruct", - "hugging_face_id": "meta-llama/Meta-Llama-3.1-405B-Instruct", - "name": "Meta: Llama 3.1 405B Instruct", - "created": 1721692800, - "description": "The highly anticipated 400B class of Llama3 is here! Clocking in at 128k context with impressive eval scores, the Meta AI team continues to push the frontier of open-source LLMs.\n\nMeta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 405B instruct-tuned version is optimized for high quality dialogue usecases.\n\nIt has demonstrated strong performance compared to leading closed-source models including GPT-4o and Claude 3.5 Sonnet in 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": 32768, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Llama3", - "instruct_type": "llama3" - }, - "pricing": { - "prompt": "0.0000008", - "completion": "0.0000008", - "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": [ - "max_tokens", - "temperature", - "top_p", - "tools", - "tool_choice", - "stop", - "frequency_penalty", - "presence_penalty", - "top_k", - "repetition_penalty", - "response_format", - "structured_outputs", - "logit_bias", - "logprobs", - "top_logprobs", - "min_p", - "seed" - ] - }, { "id": "meta-llama/llama-3.1-70b-instruct", "canonical_slug": "meta-llama/llama-3.1-70b-instruct", @@ -11406,6 +11686,104 @@ "structured_outputs" ] }, + { + "id": "meta-llama/llama-3.1-405b-instruct:free", + "canonical_slug": "meta-llama/llama-3.1-405b-instruct", + "hugging_face_id": "meta-llama/Meta-Llama-3.1-405B-Instruct", + "name": "Meta: Llama 3.1 405B Instruct (free)", + "created": 1721692800, + "description": "The highly anticipated 400B class of Llama3 is here! Clocking in at 128k context with impressive eval scores, the Meta AI team continues to push the frontier of open-source LLMs.\n\nMeta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 405B instruct-tuned version is optimized for high quality dialogue usecases.\n\nIt has demonstrated strong performance compared to leading closed-source models including GPT-4o and Claude 3.5 Sonnet in 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": 65536, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Llama3", + "instruct_type": "llama3" + }, + "pricing": { + "prompt": "0", + "completion": "0", + "request": "0", + "image": "0", + "web_search": "0", + "internal_reasoning": "0" + }, + "top_provider": { + "context_length": 65536, + "max_completion_tokens": null, + "is_moderated": false + }, + "per_request_limits": null, + "supported_parameters": [ + "max_tokens", + "temperature", + "top_p", + "structured_outputs", + "response_format", + "stop", + "frequency_penalty", + "presence_penalty", + "top_k" + ] + }, + { + "id": "meta-llama/llama-3.1-405b-instruct", + "canonical_slug": "meta-llama/llama-3.1-405b-instruct", + "hugging_face_id": "meta-llama/Meta-Llama-3.1-405B-Instruct", + "name": "Meta: Llama 3.1 405B Instruct", + "created": 1721692800, + "description": "The highly anticipated 400B class of Llama3 is here! Clocking in at 128k context with impressive eval scores, the Meta AI team continues to push the frontier of open-source LLMs.\n\nMeta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 405B instruct-tuned version is optimized for high quality dialogue usecases.\n\nIt has demonstrated strong performance compared to leading closed-source models including GPT-4o and Claude 3.5 Sonnet in 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": 32768, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Llama3", + "instruct_type": "llama3" + }, + "pricing": { + "prompt": "0.0000008", + "completion": "0.0000008", + "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": [ + "max_tokens", + "temperature", + "top_p", + "tools", + "tool_choice", + "stop", + "frequency_penalty", + "presence_penalty", + "top_k", + "repetition_penalty", + "response_format", + "structured_outputs", + "logit_bias", + "logprobs", + "top_logprobs", + "min_p", + "seed" + ] + }, { "id": "mistralai/mistral-nemo:free", "canonical_slug": "mistralai/mistral-nemo", @@ -11462,7 +11840,7 @@ "name": "Mistral: Mistral Nemo", "created": 1721347200, "description": "A 12B parameter model with a 128k token context length built by Mistral in collaboration with NVIDIA.\n\nThe model is multilingual, supporting English, French, German, Spanish, Italian, Portuguese, Chinese, Japanese, Korean, Arabic, and Hindi.\n\nIt supports function calling and is released under the Apache 2.0 license.", - "context_length": 131072, + "context_length": 32000, "architecture": { "modality": "text->text", "input_modalities": [ @@ -11475,16 +11853,16 @@ "instruct_type": "mistral" }, "pricing": { - "prompt": "0.000000008", - "completion": "0.000000001", + "prompt": "0.0000000075", + "completion": "0.00000005", "request": "0", "image": "0", "web_search": "0", "internal_reasoning": "0" }, "top_provider": { - "context_length": 131072, - "max_completion_tokens": 131072, + "context_length": 32000, + "max_completion_tokens": null, "is_moderated": false }, "per_request_limits": null, @@ -11508,6 +11886,60 @@ "structured_outputs" ] }, + { + "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": [ + "max_tokens", + "temperature", + "top_p", + "tools", + "tool_choice", + "stop", + "frequency_penalty", + "presence_penalty", + "web_search_options", + "seed", + "logit_bias", + "logprobs", + "top_logprobs", + "response_format", + "structured_outputs" + ] + }, { "id": "openai/gpt-4o-mini", "canonical_slug": "openai/gpt-4o-mini", @@ -11562,60 +11994,6 @@ "tool_choice" ] }, - { - "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": [ - "max_tokens", - "temperature", - "top_p", - "tools", - "tool_choice", - "stop", - "frequency_penalty", - "presence_penalty", - "web_search_options", - "seed", - "logit_bias", - "logprobs", - "top_logprobs", - "response_format", - "structured_outputs" - ] - }, { "id": "google/gemma-2-27b-it", "canonical_slug": "google/gemma-2-27b-it", @@ -11778,8 +12156,8 @@ "instruct_type": "gemma" }, "pricing": { - "prompt": "0.0000002", - "completion": "0.0000002", + "prompt": "0.000000004", + "completion": "0.000000004", "request": "0", "image": "0", "web_search": "0", @@ -11798,11 +12176,14 @@ "stop", "frequency_penalty", "presence_penalty", - "response_format", - "top_logprobs", + "seed", + "top_k", + "min_p", + "repetition_penalty", "logprobs", "logit_bias", - "seed" + "top_logprobs", + "response_format" ] }, { @@ -12087,6 +12468,57 @@ "response_format" ] }, + { + "id": "mistralai/mistral-7b-instruct-v0.3", + "canonical_slug": "mistralai/mistral-7b-instruct-v0.3", + "hugging_face_id": "mistralai/Mistral-7B-Instruct-v0.3", + "name": "Mistral: Mistral 7B Instruct v0.3", + "created": 1716768000, + "description": "A high-performing, industry-standard 7.3B parameter model, with optimizations for speed and context length.\n\nAn improved version of [Mistral 7B Instruct v0.2](/models/mistralai/mistral-7b-instruct-v0.2), with the following changes:\n\n- Extended vocabulary to 32768\n- Supports v3 Tokenizer\n- Supports function calling\n\nNOTE: Support for function calling depends on the provider.", + "context_length": 32768, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Mistral", + "instruct_type": "mistral" + }, + "pricing": { + "prompt": "0.000000028", + "completion": "0.000000054", + "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": [ + "max_tokens", + "temperature", + "top_p", + "stop", + "frequency_penalty", + "presence_penalty", + "top_k", + "repetition_penalty", + "logit_bias", + "min_p", + "response_format", + "seed", + "tools", + "tool_choice", + "logprobs" + ] + }, { "id": "mistralai/mistral-7b-instruct:free", "canonical_slug": "mistralai/mistral-7b-instruct", @@ -12237,57 +12669,6 @@ "top_k" ] }, - { - "id": "mistralai/mistral-7b-instruct-v0.3", - "canonical_slug": "mistralai/mistral-7b-instruct-v0.3", - "hugging_face_id": "mistralai/Mistral-7B-Instruct-v0.3", - "name": "Mistral: Mistral 7B Instruct v0.3", - "created": 1716768000, - "description": "A high-performing, industry-standard 7.3B parameter model, with optimizations for speed and context length.\n\nAn improved version of [Mistral 7B Instruct v0.2](/models/mistralai/mistral-7b-instruct-v0.2), with the following changes:\n\n- Extended vocabulary to 32768\n- Supports v3 Tokenizer\n- Supports function calling\n\nNOTE: Support for function calling depends on the provider.", - "context_length": 32768, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Mistral", - "instruct_type": "mistral" - }, - "pricing": { - "prompt": "0.000000028", - "completion": "0.000000054", - "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": [ - "max_tokens", - "temperature", - "top_p", - "stop", - "frequency_penalty", - "presence_penalty", - "top_k", - "repetition_penalty", - "logit_bias", - "min_p", - "response_format", - "seed", - "tools", - "tool_choice", - "logprobs" - ] - }, { "id": "microsoft/phi-3-mini-128k-instruct", "canonical_slug": "microsoft/phi-3-mini-128k-instruct", @@ -12456,16 +12837,116 @@ "max_tokens", "temperature", "top_p", + "tools", + "tool_choice", "stop", "frequency_penalty", "presence_penalty", - "tools", - "tool_choice", "seed", "response_format", "structured_outputs" ] }, + { + "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": [ + "max_tokens", + "temperature", + "top_p", + "tools", + "tool_choice", + "stop", + "frequency_penalty", + "presence_penalty", + "web_search_options", + "seed", + "logit_bias", + "logprobs", + "top_logprobs", + "response_format", + "structured_outputs" + ] + }, + { + "id": "meta-llama/llama-guard-2-8b", + "canonical_slug": "meta-llama/llama-guard-2-8b", + "hugging_face_id": "meta-llama/Meta-Llama-Guard-2-8B", + "name": "Meta: LlamaGuard 2 8B", + "created": 1715558400, + "description": "This safeguard model has 8B parameters and is based on the Llama 3 family. Just like is predecessor, [LlamaGuard 1](https://huggingface.co/meta-llama/LlamaGuard-7b), it can do both prompt and response classification.\n\nLlamaGuard 2 acts as a normal LLM would, generating text that indicates whether the given input/output is safe/unsafe. If deemed unsafe, it will also share the content categories violated.\n\nFor best results, please use raw prompt input or the `/completions` endpoint, instead of the chat API.\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": "none" + }, + "pricing": { + "prompt": "0.0000002", + "completion": "0.0000002", + "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": [ + "max_tokens", + "temperature", + "top_p", + "stop", + "frequency_penalty", + "presence_penalty", + "top_k", + "repetition_penalty", + "logit_bias", + "min_p", + "response_format" + ] + }, { "id": "openai/gpt-4o", "canonical_slug": "openai/gpt-4o", @@ -12573,154 +13054,6 @@ "structured_outputs" ] }, - { - "id": "meta-llama/llama-guard-2-8b", - "canonical_slug": "meta-llama/llama-guard-2-8b", - "hugging_face_id": "meta-llama/Meta-Llama-Guard-2-8B", - "name": "Meta: LlamaGuard 2 8B", - "created": 1715558400, - "description": "This safeguard model has 8B parameters and is based on the Llama 3 family. Just like is predecessor, [LlamaGuard 1](https://huggingface.co/meta-llama/LlamaGuard-7b), it can do both prompt and response classification.\n\nLlamaGuard 2 acts as a normal LLM would, generating text that indicates whether the given input/output is safe/unsafe. If deemed unsafe, it will also share the content categories violated.\n\nFor best results, please use raw prompt input or the `/completions` endpoint, instead of the chat API.\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": "none" - }, - "pricing": { - "prompt": "0.0000002", - "completion": "0.0000002", - "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": [ - "max_tokens", - "temperature", - "top_p", - "stop", - "frequency_penalty", - "presence_penalty", - "top_k", - "repetition_penalty", - "logit_bias", - "min_p", - "response_format" - ] - }, - { - "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": [ - "max_tokens", - "temperature", - "top_p", - "tools", - "tool_choice", - "stop", - "frequency_penalty", - "presence_penalty", - "web_search_options", - "seed", - "logit_bias", - "logprobs", - "top_logprobs", - "response_format", - "structured_outputs" - ] - }, - { - "id": "neversleep/llama-3-lumimaid-8b", - "canonical_slug": "neversleep/llama-3-lumimaid-8b", - "hugging_face_id": "NeverSleep/Llama-3-Lumimaid-8B-v0.1", - "name": "NeverSleep: Llama 3 Lumimaid 8B", - "created": 1714780800, - "description": "The NeverSleep team is back, with a Llama 3 8B finetune trained on their curated roleplay data. Striking a balance between eRP and RP, Lumimaid was designed to be serious, yet uncensored when necessary.\n\nTo enhance it's overall intelligence and chat capability, roughly 40% of the training data was not roleplay. This provides a breadth of knowledge to access, while still keeping roleplay as the primary strength.\n\nUsage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).", - "context_length": 24576, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Llama3", - "instruct_type": "llama3" - }, - "pricing": { - "prompt": "0.0000002", - "completion": "0.00000125", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 24576, - "max_completion_tokens": 2048, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "max_tokens", - "temperature", - "top_p", - "stop", - "frequency_penalty", - "presence_penalty", - "repetition_penalty", - "top_k", - "min_p", - "seed", - "logit_bias", - "top_a" - ] - }, { "id": "sao10k/fimbulvetr-11b-v2", "canonical_slug": "sao10k/fimbulvetr-11b-v2", @@ -12816,8 +13149,7 @@ "tool_choice", "response_format", "top_logprobs", - "logprobs", - "top_a" + "logprobs" ] }, { @@ -13010,11 +13342,11 @@ "max_tokens", "temperature", "top_p", + "tools", + "tool_choice", "stop", "frequency_penalty", "presence_penalty", - "tools", - "tool_choice", "seed", "response_format", "structured_outputs" @@ -13211,52 +13543,6 @@ "logit_bias" ] }, - { - "id": "cohere/command", - "canonical_slug": "cohere/command", - "hugging_face_id": null, - "name": "Cohere: Command", - "created": 1710374400, - "description": "Command is an instruction-following conversational model that performs language tasks with high quality, more reliably and with a longer context than our base generative models.\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": 4096, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Cohere", - "instruct_type": null - }, - "pricing": { - "prompt": "0.000001", - "completion": "0.000002", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 4096, - "max_completion_tokens": 4000, - "is_moderated": true - }, - "per_request_limits": null, - "supported_parameters": [ - "max_tokens", - "temperature", - "top_p", - "stop", - "frequency_penalty", - "presence_penalty", - "top_k", - "seed", - "response_format", - "structured_outputs" - ] - }, { "id": "cohere/command-r", "canonical_slug": "cohere/command-r", @@ -13304,6 +13590,52 @@ "structured_outputs" ] }, + { + "id": "cohere/command", + "canonical_slug": "cohere/command", + "hugging_face_id": null, + "name": "Cohere: Command", + "created": 1710374400, + "description": "Command is an instruction-following conversational model that performs language tasks with high quality, more reliably and with a longer context than our base generative models.\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": 4096, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Cohere", + "instruct_type": null + }, + "pricing": { + "prompt": "0.000001", + "completion": "0.000002", + "request": "0", + "image": "0", + "web_search": "0", + "internal_reasoning": "0" + }, + "top_provider": { + "context_length": 4096, + "max_completion_tokens": 4000, + "is_moderated": true + }, + "per_request_limits": null, + "supported_parameters": [ + "max_tokens", + "temperature", + "top_p", + "stop", + "frequency_penalty", + "presence_penalty", + "top_k", + "seed", + "response_format", + "structured_outputs" + ] + }, { "id": "anthropic/claude-3-haiku:beta", "canonical_slug": "anthropic/claude-3-haiku", @@ -13674,56 +14006,6 @@ "structured_outputs" ] }, - { - "id": "openai/gpt-3.5-turbo-0613", - "canonical_slug": "openai/gpt-3.5-turbo-0613", - "hugging_face_id": null, - "name": "OpenAI: GPT-3.5 Turbo (older v0613)", - "created": 1706140800, - "description": "GPT-3.5 Turbo is OpenAI's fastest model. It can understand and generate natural language or code, and is optimized for chat and traditional completion tasks.\n\nTraining data up to Sep 2021.", - "context_length": 4095, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "GPT", - "instruct_type": null - }, - "pricing": { - "prompt": "0.000001", - "completion": "0.000002", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 4095, - "max_completion_tokens": 4096, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "max_tokens", - "temperature", - "top_p", - "tools", - "tool_choice", - "stop", - "frequency_penalty", - "presence_penalty", - "seed", - "logit_bias", - "logprobs", - "top_logprobs", - "response_format", - "structured_outputs" - ] - }, { "id": "openai/gpt-4-turbo-preview", "canonical_slug": "openai/gpt-4-turbo-preview", @@ -13774,6 +14056,56 @@ "structured_outputs" ] }, + { + "id": "openai/gpt-3.5-turbo-0613", + "canonical_slug": "openai/gpt-3.5-turbo-0613", + "hugging_face_id": null, + "name": "OpenAI: GPT-3.5 Turbo (older v0613)", + "created": 1706140800, + "description": "GPT-3.5 Turbo is OpenAI's fastest model. It can understand and generate natural language or code, and is optimized for chat and traditional completion tasks.\n\nTraining data up to Sep 2021.", + "context_length": 4095, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "GPT", + "instruct_type": null + }, + "pricing": { + "prompt": "0.000001", + "completion": "0.000002", + "request": "0", + "image": "0", + "web_search": "0", + "internal_reasoning": "0" + }, + "top_provider": { + "context_length": 4095, + "max_completion_tokens": 4096, + "is_moderated": false + }, + "per_request_limits": null, + "supported_parameters": [ + "max_tokens", + "temperature", + "top_p", + "tools", + "tool_choice", + "stop", + "frequency_penalty", + "presence_penalty", + "seed", + "logit_bias", + "logprobs", + "top_logprobs", + "response_format", + "structured_outputs" + ] + }, { "id": "nousresearch/nous-hermes-2-mixtral-8x7b-dpo", "canonical_slug": "nousresearch/nous-hermes-2-mixtral-8x7b-dpo", @@ -13822,12 +14154,12 @@ ] }, { - "id": "mistralai/mistral-small", - "canonical_slug": "mistralai/mistral-small", + "id": "mistralai/mistral-tiny", + "canonical_slug": "mistralai/mistral-tiny", "hugging_face_id": null, - "name": "Mistral Small", + "name": "Mistral Tiny", "created": 1704844800, - "description": "With 22 billion parameters, Mistral Small v24.09 offers a convenient mid-point between (Mistral NeMo 12B)[/mistralai/mistral-nemo] and (Mistral Large 2)[/mistralai/mistral-large], providing a cost-effective solution that can be deployed across various platforms and environments. It has better reasoning, exhibits more capabilities, can produce and reason about code, and is multiligual, supporting English, French, German, Italian, and Spanish.", + "description": "Note: This model is being deprecated. Recommended replacement is the newer [Ministral 8B](/mistral/ministral-8b)\n\nThis model is currently powered by Mistral-7B-v0.2, and incorporates a \"better\" fine-tuning than [Mistral 7B](/models/mistralai/mistral-7b-instruct-v0.1), inspired by community work. It's best used for large batch processing tasks where cost is a significant factor but reasoning capabilities are not crucial.", "context_length": 32768, "architecture": { "modality": "text->text", @@ -13841,8 +14173,8 @@ "instruct_type": null }, "pricing": { - "prompt": "0.0000002", - "completion": "0.0000006", + "prompt": "0.00000025", + "completion": "0.00000025", "request": "0", "image": "0", "web_search": "0", @@ -13869,12 +14201,12 @@ ] }, { - "id": "mistralai/mistral-tiny", - "canonical_slug": "mistralai/mistral-tiny", + "id": "mistralai/mistral-small", + "canonical_slug": "mistralai/mistral-small", "hugging_face_id": null, - "name": "Mistral Tiny", + "name": "Mistral Small", "created": 1704844800, - "description": "Note: This model is being deprecated. Recommended replacement is the newer [Ministral 8B](/mistral/ministral-8b)\n\nThis model is currently powered by Mistral-7B-v0.2, and incorporates a \"better\" fine-tuning than [Mistral 7B](/models/mistralai/mistral-7b-instruct-v0.1), inspired by community work. It's best used for large batch processing tasks where cost is a significant factor but reasoning capabilities are not crucial.", + "description": "With 22 billion parameters, Mistral Small v24.09 offers a convenient mid-point between (Mistral NeMo 12B)[/mistralai/mistral-nemo] and (Mistral Large 2)[/mistralai/mistral-large], providing a cost-effective solution that can be deployed across various platforms and environments. It has better reasoning, exhibits more capabilities, can produce and reason about code, and is multiligual, supporting English, French, German, Italian, and Spanish.", "context_length": 32768, "architecture": { "modality": "text->text", @@ -13888,8 +14220,8 @@ "instruct_type": null }, "pricing": { - "prompt": "0.00000025", - "completion": "0.00000025", + "prompt": "0.0000002", + "completion": "0.0000006", "request": "0", "image": "0", "web_search": "0", @@ -14224,52 +14556,6 @@ "stop" ] }, - { - "id": "undi95/toppy-m-7b", - "canonical_slug": "undi95/toppy-m-7b", - "hugging_face_id": "Undi95/Toppy-M-7B", - "name": "Toppy M 7B", - "created": 1699574400, - "description": "A wild 7B parameter model that merges several models using the new task_arithmetic merge method from mergekit.\nList of merged models:\n- NousResearch/Nous-Capybara-7B-V1.9\n- [HuggingFaceH4/zephyr-7b-beta](/models/huggingfaceh4/zephyr-7b-beta)\n- lemonilia/AshhLimaRP-Mistral-7B\n- Vulkane/120-Days-of-Sodom-LoRA-Mistral-7b\n- Undi95/Mistral-pippa-sharegpt-7b-qlora\n\n#merge #uncensored", - "context_length": 4096, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "Mistral", - "instruct_type": "alpaca" - }, - "pricing": { - "prompt": "0.0000008", - "completion": "0.0000012", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 4096, - "max_completion_tokens": 4096, - "is_moderated": false - }, - "per_request_limits": null, - "supported_parameters": [ - "max_tokens", - "temperature", - "top_p", - "stop", - "frequency_penalty", - "presence_penalty", - "repetition_penalty", - "top_k", - "min_p", - "seed" - ] - }, { "id": "alpindale/goliath-120b", "canonical_slug": "alpindale/goliath-120b", @@ -14320,6 +14606,52 @@ "top_a" ] }, + { + "id": "undi95/toppy-m-7b", + "canonical_slug": "undi95/toppy-m-7b", + "hugging_face_id": "Undi95/Toppy-M-7B", + "name": "Toppy M 7B", + "created": 1699574400, + "description": "A wild 7B parameter model that merges several models using the new task_arithmetic merge method from mergekit.\nList of merged models:\n- NousResearch/Nous-Capybara-7B-V1.9\n- [HuggingFaceH4/zephyr-7b-beta](/models/huggingfaceh4/zephyr-7b-beta)\n- lemonilia/AshhLimaRP-Mistral-7B\n- Vulkane/120-Days-of-Sodom-LoRA-Mistral-7b\n- Undi95/Mistral-pippa-sharegpt-7b-qlora\n\n#merge #uncensored", + "context_length": 4096, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "Mistral", + "instruct_type": "alpaca" + }, + "pricing": { + "prompt": "0.0000008", + "completion": "0.0000012", + "request": "0", + "image": "0", + "web_search": "0", + "internal_reasoning": "0" + }, + "top_provider": { + "context_length": 4096, + "max_completion_tokens": 4096, + "is_moderated": false + }, + "per_request_limits": null, + "supported_parameters": [ + "max_tokens", + "temperature", + "top_p", + "stop", + "frequency_penalty", + "presence_penalty", + "repetition_penalty", + "top_k", + "min_p", + "seed" + ] + }, { "id": "openrouter/auto", "canonical_slug": "openrouter/auto", @@ -14401,53 +14733,6 @@ "structured_outputs" ] }, - { - "id": "openai/gpt-3.5-turbo-instruct", - "canonical_slug": "openai/gpt-3.5-turbo-instruct", - "hugging_face_id": null, - "name": "OpenAI: GPT-3.5 Turbo Instruct", - "created": 1695859200, - "description": "This model is a variant of GPT-3.5 Turbo tuned for instructional prompts and omitting chat-related optimizations. Training data: up to Sep 2021.", - "context_length": 4095, - "architecture": { - "modality": "text->text", - "input_modalities": [ - "text" - ], - "output_modalities": [ - "text" - ], - "tokenizer": "GPT", - "instruct_type": "chatml" - }, - "pricing": { - "prompt": "0.0000015", - "completion": "0.000002", - "request": "0", - "image": "0", - "web_search": "0", - "internal_reasoning": "0" - }, - "top_provider": { - "context_length": 4095, - "max_completion_tokens": 4096, - "is_moderated": true - }, - "per_request_limits": null, - "supported_parameters": [ - "max_tokens", - "temperature", - "top_p", - "stop", - "frequency_penalty", - "presence_penalty", - "seed", - "logit_bias", - "logprobs", - "top_logprobs", - "response_format" - ] - }, { "id": "mistralai/mistral-7b-instruct-v0.1", "canonical_slug": "mistralai/mistral-7b-instruct-v0.1", @@ -14498,6 +14783,53 @@ "seed" ] }, + { + "id": "openai/gpt-3.5-turbo-instruct", + "canonical_slug": "openai/gpt-3.5-turbo-instruct", + "hugging_face_id": null, + "name": "OpenAI: GPT-3.5 Turbo Instruct", + "created": 1695859200, + "description": "This model is a variant of GPT-3.5 Turbo tuned for instructional prompts and omitting chat-related optimizations. Training data: up to Sep 2021.", + "context_length": 4095, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "GPT", + "instruct_type": "chatml" + }, + "pricing": { + "prompt": "0.0000015", + "completion": "0.000002", + "request": "0", + "image": "0", + "web_search": "0", + "internal_reasoning": "0" + }, + "top_provider": { + "context_length": 4095, + "max_completion_tokens": 4096, + "is_moderated": true + }, + "per_request_limits": null, + "supported_parameters": [ + "max_tokens", + "temperature", + "top_p", + "stop", + "frequency_penalty", + "presence_penalty", + "seed", + "logit_bias", + "logprobs", + "top_logprobs", + "response_format" + ] + }, { "id": "pygmalionai/mythalion-13b", "canonical_slug": "pygmalionai/mythalion-13b", @@ -14730,7 +15062,7 @@ "name": "ReMM SLERP 13B", "created": 1689984000, "description": "A recreation trial of the original MythoMax-L2-B13 but with updated models. #merge", - "context_length": 4096, + "context_length": 6144, "architecture": { "modality": "text->text", "input_modalities": [ @@ -14743,16 +15075,16 @@ "instruct_type": "alpaca" }, "pricing": { - "prompt": "0.0000008", - "completion": "0.0000012", + "prompt": "0.0000007", + "completion": "0.000001", "request": "0", "image": "0", "web_search": "0", "internal_reasoning": "0" }, "top_provider": { - "context_length": 4096, - "max_completion_tokens": 4096, + "context_length": 6144, + "max_completion_tokens": null, "is_moderated": false }, "per_request_limits": null, @@ -14763,6 +15095,8 @@ "stop", "frequency_penalty", "presence_penalty", + "response_format", + "structured_outputs", "repetition_penalty", "top_k", "min_p", @@ -14791,8 +15125,8 @@ "instruct_type": "alpaca" }, "pricing": { - "prompt": "0.000000065", - "completion": "0.000000065", + "prompt": "0.00000006", + "completion": "0.00000006", "request": "0", "image": "0", "web_search": "0", @@ -14800,7 +15134,7 @@ }, "top_provider": { "context_length": 4096, - "max_completion_tokens": 4096, + "max_completion_tokens": null, "is_moderated": false }, "per_request_limits": null, @@ -14808,15 +15142,16 @@ "max_tokens", "temperature", "top_p", - "presence_penalty", "frequency_penalty", - "repetition_penalty", - "top_k", - "stop", - "seed", "min_p", - "logit_bias", + "presence_penalty", + "repetition_penalty", + "seed", + "stop", + "top_k", "response_format", + "structured_outputs", + "logit_bias", "top_a" ] }, @@ -14869,6 +15204,55 @@ "response_format" ] }, + { + "id": "openai/gpt-3.5-turbo", + "canonical_slug": "openai/gpt-3.5-turbo", + "hugging_face_id": null, + "name": "OpenAI: GPT-3.5 Turbo", + "created": 1685232000, + "description": "GPT-3.5 Turbo is OpenAI's fastest model. It can understand and generate natural language or code, and is optimized for chat and traditional completion tasks.\n\nTraining data up to Sep 2021.", + "context_length": 16385, + "architecture": { + "modality": "text->text", + "input_modalities": [ + "text" + ], + "output_modalities": [ + "text" + ], + "tokenizer": "GPT", + "instruct_type": null + }, + "pricing": { + "prompt": "0.0000005", + "completion": "0.0000015", + "request": "0", + "image": "0", + "web_search": "0", + "internal_reasoning": "0" + }, + "top_provider": { + "context_length": 16385, + "max_completion_tokens": 4096, + "is_moderated": true + }, + "per_request_limits": null, + "supported_parameters": [ + "max_tokens", + "temperature", + "top_p", + "tools", + "tool_choice", + "stop", + "frequency_penalty", + "presence_penalty", + "seed", + "logit_bias", + "logprobs", + "top_logprobs", + "response_format" + ] + }, { "id": "openai/gpt-4-0314", "canonical_slug": "openai/gpt-4-0314", diff --git a/packages/kbot/dist-in/src/models/cache/openai.ts b/packages/kbot/dist-in/src/models/cache/openai.ts index f45bb40e..58b62da7 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 = [{"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":"o4-mini-deep-research-2025-06-26","object":"model","created":1750866121,"owned_by":"system"},{"id":"codex-mini-latest","object":"model","created":1746673257,"owned_by":"system"},{"id":"gpt-4o-realtime-preview-2025-06-03","object":"model","created":1748907838,"owned_by":"system"},{"id":"gpt-4o-audio-preview-2025-06-03","object":"model","created":1748908498,"owned_by":"system"},{"id":"o4-mini-deep-research","object":"model","created":1749685485,"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":"o1-preview-2024-09-12","object":"model","created":1725648865,"owned_by":"system"},{"id":"o1-preview","object":"model","created":1725648897,"owned_by":"system"},{"id":"o1-mini-2024-09-12","object":"model","created":1725648979,"owned_by":"system"},{"id":"o1-mini","object":"model","created":1725649008,"owned_by":"system"},{"id":"gpt-4o-realtime-preview-2024-10-01","object":"model","created":1727131766,"owned_by":"system"},{"id":"gpt-4o-audio-preview-2024-10-01","object":"model","created":1727389042,"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-4.5-preview","object":"model","created":1740623059,"owned_by":"system"},{"id":"gpt-4.5-preview-2025-02-27","object":"model","created":1740623304,"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-pr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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":"o4-mini-deep-research-2025-06-26","object":"model","created":1750866121,"owned_by":"system"},{"id":"codex-mini-latest","object":"model","created":1746673257,"owned_by":"system"},{"id":"gpt-4o-realtime-preview-2025-06-03","object":"model","created":1748907838,"owned_by":"system"},{"id":"gpt-4o-audio-preview-2025-06-03","object":"model","created":1748908498,"owned_by":"system"},{"id":"o4-mini-deep-research","object":"model","created":1749685485,"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":"o1-preview-2024-09-12","object":"model","created":1725648865,"owned_by":"system"},{"id":"o1-preview","object":"model","created":1725648897,"owned_by":"system"},{"id":"o1-mini-2024-09-12","object":"model","created":1725648979,"owned_by":"system"},{"id":"o1-mini","object":"model","created":1725649008,"owned_by":"system"},{"id":"gpt-4o-realtime-preview-2024-10-01","object":"model","created":1727131766,"owned_by":"system"},{"id":"gpt-4o-audio-preview-2024-10-01","object":"model","created":1727389042,"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":"o4-mini-2025-04-16","object":"model","created":1744133506,"owned_by":"system"},{"id":"o4-mini","object":"model","created":1744225351,"owned_by":"system"},{"id":"gpt-4.1-2025-04-14","object":"model","created":1744315746,"owned_by":"system"},{"id":"gpt-4.1","object":"model","created":1744316542,"owned_by":"system"},{"id":"gpt-4.1-mini-2025-04-14","object":"model","created":1744317547,"owned_by":"system"},{"id":"gpt-4.1-mini","object":"model","created":1744318173,"owned_by":"system"},{"id":"gpt-4.1-nano-2025-04-14","object":"model","created":1744321025,"owned_by":"system"},{"id":"gpt-4.1-nano","object":"model","created":1744321707,"owned_by":"system"},{"id":"gpt-image-1","object":"model","created":1745517030,"owned_by":"system"},{"id":"gpt-3.5-turbo-16k","object":"model","created":1683758102,"owned_by":"openai-internal"},{"id":"tts-1","object":"model","created":1681940951,"owned_by":"openai-internal"},{"id":"whisper-1","object":"model","created":1677532384,"owned_by":"openai-internal"},{"id":"text-embedding-ada-002","object":"model","created":1671217299,"owned_by":"openai-internal"}] \ No newline at end of file diff --git a/packages/kbot/dist-in/src/models/cache/openrouter.ts b/packages/kbot/dist-in/src/models/cache/openrouter.ts index 057159c5..82de1206 100644 --- a/packages/kbot/dist-in/src/models/cache/openrouter.ts +++ b/packages/kbot/dist-in/src/models/cache/openrouter.ts @@ -1 +1 @@ -export const models = [{"id":"openrouter/cypher-alpha:free","name":"Cypher Alpha (free)","pricing":{"prompt":"0","completion":"0","request":"0","image":"0","web_search":"0","internal_reasoning":"0"},"created":1751336087,"top_provider":{"context_length":1000000,"max_completion_tokens":10000,"is_moderated":false}},{"id":"baidu/ernie-4.5-300b-a47b","name":"Baidu: ERNIE 4.5 300B A47B ","pricing":{"prompt":"0.00000028","completion":"0.0000011","request":"0","image":"0","web_search":"0","internal_reasoning":"0"},"created":1751300139,"top_provider":{"context_length":123000,"max_completion_tokens":12000,"is_moderated":false}},{"id":"thedrummer/anubis-70b-v1.1","name":"TheDrummer: Anubis 70B V1.1","pricing":{"prompt":"0.0000003","completion":"0.0000008","request":"0","image":"0","web_search":"0","internal_reasoning":"0"},"created":1751208347,"top_provider":{"context_length":131072,"max_completion_tokens":131072,"is_moderated":false}},{"id":"inception/mercury","name":"Inception: Mercury","pricing":{"prompt":"0.00000025","completion":"0.000001","request":"0","image":"0","web_search":"0","internal_reasoning":"0"},"created":1750973026,"top_provider":{"context_length":32000,"max_completion_tokens":16000,"is_moderated":false}},{"id":"morph/morph-v2","name":"Morph: Fast Apply","pricing":{"prompt":"0.0000012","completion":"0.0000027","request":"0","image":"0","web_search":"0","internal_reasoning":"0"},"created":1750946108,"top_provider":{"context_length":32000,"max_completion_tokens":16000,"is_moderated":false}},{"id":"mistralai/mistral-small-3.2-24b-instruct:free","name":"Mistral: Mistral Small 3.2 24B (free)","pricing":{"prompt":"0","completion":"0","request":"0","image":"0","web_search":"0","internal_reasoning":"0"},"created":1750443016,"top_provider":{"context_length":96000,"max_completion_tokens":null,"is_moderated":false}},{"id":"mistralai/mistral-small-3.2-24b-instruct","name":"Mistral: Mistral Small 3.2 24B","pricing":{"prompt":"0.00000005","completion":"0.0000001","request":"0","image":"0","web_search":"0","internal_reasoning":"0"},"created":1750443016,"top_provider":{"context_length":128000,"max_completion_tokens":null,"is_moderated":false}},{"id":"minimax/minimax-m1","name":"MiniMax: MiniMax M1","pricing":{"prompt":"0.0000003","completion":"0.00000165","request":"0","image":"0","web_search":"0","internal_reasoning":"0"},"created":1750200414,"top_provider":{"context_length":1000000,"max_completion_tokens":40000,"is_moderated":false}},{"id":"google/gemini-2.5-flash-lite-preview-06-17","name":"Google: Gemini 2.5 Flash Lite Preview 06-17","pricing":{"prompt":"0.0000001","completion":"0.0000004","request":"0","image":"0","web_search":"0","internal_reasoning":"0"},"created":1750173831,"top_provider":{"context_length":1048576,"max_completion_tokens":65535,"is_moderated":false}},{"id":"google/gemini-2.5-flash","name":"Google: Gemini 2.5 Flash","pricing":{"prompt":"0.0000003","completion":"0.0000025","request":"0","image":"0.001238","web_search":"0","internal_reasoning":"0","input_cache_read":"0.000000075","input_cache_write":"0.0000003833"},"created":1750172488,"top_provider":{"context_length":1048576,"max_completion_tokens":65535,"is_moderated":false}},{"id":"google/gemini-2.5-pro","name":"Google: Gemini 2.5 Pro","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"},"created":1750169544,"top_provider":{"context_length":1048576,"max_completion_tokens":65536,"is_moderated":false}},{"id":"moonshotai/kimi-dev-72b:free","name":"Kimi Dev 72b (free)","pricing":{"prompt":"0","completion":"0","request":"0","image":"0","web_search":"0","internal_reasoning":"0"},"created":1750115909,"top_provider":{"context_length":131072,"max_completion_tokens":null,"is_moderated":false}},{"id":"openai/o3-pro","name":"OpenAI: o3 Pro","pricing":{"prompt":"0.00002","completion":"0.00008","request":"0","image":"0.0153","web_search":"0","internal_reasoning":"0"},"created":1749598352,"top_provider":{"context_length":200000,"max_completion_tokens":100000,"is_moderated":true}},{"id":"x-ai/grok-3-mini","name":"xAI: Grok 3 Mini","pricing":{"prompt":"0.0000003","completion":"0.0000005","request":"0","image":"0","web_search":"0","internal_reasoning":"0","input_cache_read":"0.000000075"},"created":1749583245,"top_provider":{"context_length":131072,"max_completion_tokens":null,"is_moderated":false}},{"id":"x-ai/grok-3","name":"xAI: Grok 3","pricing":{"prompt":"0.000003","completion":"0.000015","request":"0","image":"0","web_search":"0","internal_reasoning":"0","input_cache_read":"0.00000075"},"created":1749582908,"top_provider":{"context_length":131072,"max_completion_tokens":null,"is_moderated":false}},{"id":"mistralai/magistral-small-2506","name":"Mistral: Magistral Small 2506","pricing":{"prompt":"0.0000005","completion":"0.0000015","request":"0","image":"0","web_search":"0","internal_reasoning":"0"},"created":1749569561,"top_provider":{"context_length":40000,"max_completion_tokens":40000,"is_moderated":false}},{"id":"mistralai/magistral-medium-2506","name":"Mistral: Magistral Medium 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06-05","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"},"created":1749137257,"top_provider":{"context_length":1048576,"max_completion_tokens":65536,"is_moderated":false}},{"id":"deepseek/deepseek-r1-distill-qwen-7b","name":"DeepSeek: R1 Distill Qwen 7B","pricing":{"prompt":"0.0000001","completion":"0.0000002","request":"0","image":"0","web_search":"0","internal_reasoning":"0"},"created":1748628237,"top_provider":{"context_length":131072,"max_completion_tokens":null,"is_moderated":false}},{"id":"deepseek/deepseek-r1-0528-qwen3-8b:free","name":"DeepSeek: Deepseek R1 0528 Qwen3 8B 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a/packages/kbot/dist/main_node.js +++ b/packages/kbot/dist/main_node.js @@ -179512,11 +179512,13 @@ var E_OPENAI_MODEL; ;// ./dist-in/models/cache/openrouter-models.js var E_OPENROUTER_MODEL; (function (E_OPENROUTER_MODEL) { + E_OPENROUTER_MODEL["MODEL_OPENROUTER_CYPHER_ALPHA_FREE"] = "openrouter/cypher-alpha:free"; + 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_MORPH_MORPH_V2"] = "morph/morph-v2"; 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_EXTENDED"] = "minimax/minimax-m1:extended"; 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"; @@ -179529,7 +179531,6 @@ var E_OPENROUTER_MODEL; 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_SENTIENTAGI_DOBBY_MINI_UNHINGED_PLUS_LLAMA_3_1_8B"] = "sentientagi/dobby-mini-unhinged-plus-llama-3.1-8b"; E_OPENROUTER_MODEL["MODEL_DEEPSEEK_DEEPSEEK_R1_DISTILL_QWEN_7B"] = "deepseek/deepseek-r1-distill-qwen-7b"; 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"; @@ -179556,9 +179557,8 @@ var E_OPENROUTER_MODEL; E_OPENROUTER_MODEL["MODEL_ARCEE_AI_VIRTUOSO_MEDIUM_V2"] = "arcee-ai/virtuoso-medium-v2"; E_OPENROUTER_MODEL["MODEL_ARCEE_AI_ARCEE_BLITZ"] = "arcee-ai/arcee-blitz"; E_OPENROUTER_MODEL["MODEL_MICROSOFT_PHI_4_REASONING_PLUS"] = "microsoft/phi-4-reasoning-plus"; - E_OPENROUTER_MODEL["MODEL_INCEPTION_MERCURY_CODER_SMALL_BETA"] = "inception/mercury-coder-small-beta"; + E_OPENROUTER_MODEL["MODEL_INCEPTION_MERCURY_CODER"] = "inception/mercury-coder"; E_OPENROUTER_MODEL["MODEL_OPENGVLAB_INTERNVL3_14B"] = "opengvlab/internvl3-14b"; - E_OPENROUTER_MODEL["MODEL_OPENGVLAB_INTERNVL3_2B"] = "opengvlab/internvl3-2b"; 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"; @@ -179572,10 +179572,8 @@ var E_OPENROUTER_MODEL; 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_THUDM_GLM_Z1_RUMINATION_32B"] = "thudm/glm-z1-rumination-32b"; E_OPENROUTER_MODEL["MODEL_MICROSOFT_MAI_DS_R1_FREE"] = "microsoft/mai-ds-r1:free"; E_OPENROUTER_MODEL["MODEL_THUDM_GLM_Z1_32B_FREE"] = "thudm/glm-z1-32b:free"; - E_OPENROUTER_MODEL["MODEL_THUDM_GLM_Z1_32B"] = "thudm/glm-z1-32b"; E_OPENROUTER_MODEL["MODEL_THUDM_GLM_4_32B_FREE"] = "thudm/glm-4-32b:free"; E_OPENROUTER_MODEL["MODEL_THUDM_GLM_4_32B"] = "thudm/glm-4-32b"; E_OPENROUTER_MODEL["MODEL_GOOGLE_GEMINI_2_5_FLASH_PREVIEW"] = "google/gemini-2.5-flash-preview"; @@ -179638,8 +179636,8 @@ var E_OPENROUTER_MODEL; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4_5_PREVIEW"] = "openai/gpt-4.5-preview"; 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_BETA"] = "anthropic/claude-3.7-sonnet:beta"; E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_3_7_SONNET_THINKING"] = "anthropic/claude-3.7-sonnet:thinking"; + E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_3_7_SONNET_BETA"] = "anthropic/claude-3.7-sonnet:beta"; E_OPENROUTER_MODEL["MODEL_PERPLEXITY_R1_1776"] = "perplexity/r1-1776"; 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"; @@ -179707,34 +179705,32 @@ var E_OPENROUTER_MODEL; E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_3_5_HAIKU"] = "anthropic/claude-3.5-haiku"; E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_3_5_HAIKU_20241022_BETA"] = "anthropic/claude-3.5-haiku-20241022:beta"; E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_3_5_HAIKU_20241022"] = "anthropic/claude-3.5-haiku-20241022"; + E_OPENROUTER_MODEL["MODEL_NEVERSLEEP_LLAMA_3_1_LUMIMAID_70B"] = "neversleep/llama-3.1-lumimaid-70b"; + E_OPENROUTER_MODEL["MODEL_ANTHRACITE_ORG_MAGNUM_V4_72B"] = "anthracite-org/magnum-v4-72b"; E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_3_5_SONNET_BETA"] = "anthropic/claude-3.5-sonnet:beta"; E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_3_5_SONNET"] = "anthropic/claude-3.5-sonnet"; - E_OPENROUTER_MODEL["MODEL_ANTHRACITE_ORG_MAGNUM_V4_72B"] = "anthracite-org/magnum-v4-72b"; - E_OPENROUTER_MODEL["MODEL_NEVERSLEEP_LLAMA_3_1_LUMIMAID_70B"] = "neversleep/llama-3.1-lumimaid-70b"; - E_OPENROUTER_MODEL["MODEL_X_AI_GROK_BETA"] = "x-ai/grok-beta"; 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_PI"] = "inflection/inflection-3-pi"; 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_LIQUID_LFM_40B"] = "liquid/lfm-40b"; - E_OPENROUTER_MODEL["MODEL_ANTHRACITE_ORG_MAGNUM_V2_72B"] = "anthracite-org/magnum-v2-72b"; 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_LIQUID_LFM_40B"] = "liquid/lfm-40b"; 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_FREE"] = "meta-llama/llama-3.2-11b-vision-instruct:free"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_2_11B_VISION_INSTRUCT"] = "meta-llama/llama-3.2-11b-vision-instruct"; - E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_2_1B_INSTRUCT_FREE"] = "meta-llama/llama-3.2-1b-instruct:free"; - E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_2_1B_INSTRUCT"] = "meta-llama/llama-3.2-1b-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_PREVIEW"] = "openai/o1-preview"; - E_OPENROUTER_MODEL["MODEL_OPENAI_O1_MINI_2024_09_12"] = "openai/o1-mini-2024-09-12"; E_OPENROUTER_MODEL["MODEL_OPENAI_O1_PREVIEW_2024_09_12"] = "openai/o1-preview-2024-09-12"; 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"; @@ -179744,17 +179740,16 @@ var E_OPENROUTER_MODEL; 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"] = "nousresearch/hermes-3-llama-3.1-405b"; E_OPENROUTER_MODEL["MODEL_OPENAI_CHATGPT_4O_LATEST"] = "openai/chatgpt-4o-latest"; - E_OPENROUTER_MODEL["MODEL_AETHERWIING_MN_STARCANNON_12B"] = "aetherwiing/mn-starcannon-12b"; E_OPENROUTER_MODEL["MODEL_SAO10K_L3_LUNARIS_8B"] = "sao10k/l3-lunaris-8b"; + E_OPENROUTER_MODEL["MODEL_AETHERWIING_MN_STARCANNON_12B"] = "aetherwiing/mn-starcannon-12b"; E_OPENROUTER_MODEL["MODEL_OPENAI_GPT_4O_2024_08_06"] = "openai/gpt-4o-2024-08-06"; - E_OPENROUTER_MODEL["MODEL_NOTHINGIISREAL_MN_CELESTE_12B"] = "nothingiisreal/mn-celeste-12b"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_1_405B"] = "meta-llama/llama-3.1-405b"; + E_OPENROUTER_MODEL["MODEL_NOTHINGIISREAL_MN_CELESTE_12B"] = "nothingiisreal/mn-celeste-12b"; E_OPENROUTER_MODEL["MODEL_PERPLEXITY_LLAMA_3_1_SONAR_SMALL_128K_ONLINE"] = "perplexity/llama-3.1-sonar-small-128k-online"; E_OPENROUTER_MODEL["MODEL_PERPLEXITY_LLAMA_3_1_SONAR_LARGE_128K_ONLINE"] = "perplexity/llama-3.1-sonar-large-128k-online"; + E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_1_8B_INSTRUCT"] = "meta-llama/llama-3.1-8b-instruct"; 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_META_LLAMA_LLAMA_3_1_8B_INSTRUCT_FREE"] = "meta-llama/llama-3.1-8b-instruct:free"; - E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_1_8B_INSTRUCT"] = "meta-llama/llama-3.1-8b-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"; @@ -179769,31 +179764,31 @@ var E_OPENROUTER_MODEL; E_OPENROUTER_MODEL["MODEL_SAO10K_L3_EURYALE_70B"] = "sao10k/l3-euryale-70b"; E_OPENROUTER_MODEL["MODEL_COGNITIVECOMPUTATIONS_DOLPHIN_MIXTRAL_8X22B"] = "cognitivecomputations/dolphin-mixtral-8x22b"; E_OPENROUTER_MODEL["MODEL_QWEN_QWEN_2_72B_INSTRUCT"] = "qwen/qwen-2-72b-instruct"; - E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_7B_INSTRUCT_V0_3"] = "mistralai/mistral-7b-instruct-v0.3"; - 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"; E_OPENROUTER_MODEL["MODEL_MISTRALAI_MISTRAL_7B_INSTRUCT"] = "mistralai/mistral-7b-instruct"; + 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_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_2024_05_13"] = "openai/gpt-4o-2024-05-13"; - E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_GUARD_2_8B"] = "meta-llama/llama-guard-2-8b"; 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_NEVERSLEEP_LLAMA_3_LUMIMAID_8B"] = "neversleep/llama-3-lumimaid-8b"; E_OPENROUTER_MODEL["MODEL_SAO10K_FIMBULVETR_11B_V2"] = "sao10k/fimbulvetr-11b-v2"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_8B_INSTRUCT"] = "meta-llama/llama-3-8b-instruct"; E_OPENROUTER_MODEL["MODEL_META_LLAMA_LLAMA_3_70B_INSTRUCT"] = "meta-llama/llama-3-70b-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_OPENAI_GPT_4_TURBO"] = "openai/gpt-4-turbo"; 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_SOPHOSYMPATHEIA_MIDNIGHT_ROSE_70B"] = "sophosympatheia/midnight-rose-70b"; - E_OPENROUTER_MODEL["MODEL_COHERE_COMMAND_R"] = "cohere/command-r"; 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_BETA"] = "anthropic/claude-3-haiku:beta"; E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_3_HAIKU"] = "anthropic/claude-3-haiku"; E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_3_OPUS_BETA"] = "anthropic/claude-3-opus:beta"; @@ -179810,10 +179805,10 @@ var E_OPENROUTER_MODEL; 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_ANTHROPIC_CLAUDE_2_BETA"] = "anthropic/claude-2:beta"; - E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_2"] = "anthropic/claude-2"; E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_2_1_BETA"] = "anthropic/claude-2.1:beta"; E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_2_1"] = "anthropic/claude-2.1"; + E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_2_BETA"] = "anthropic/claude-2:beta"; + E_OPENROUTER_MODEL["MODEL_ANTHROPIC_CLAUDE_2"] = "anthropic/claude-2"; E_OPENROUTER_MODEL["MODEL_UNDI95_TOPPY_M_7B"] = "undi95/toppy-m-7b"; E_OPENROUTER_MODEL["MODEL_ALPINDALE_GOLIATH_120B"] = "alpindale/goliath-120b"; E_OPENROUTER_MODEL["MODEL_OPENROUTER_AUTO"] = "openrouter/auto"; @@ -179830,12 +179825,12 @@ var E_OPENROUTER_MODEL; 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 || (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_OPENROUTER_CYPHER_ALPHA_FREE"] = "openrouter/cypher-alpha: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_MINIMAX_MINIMAX_M1_EXTENDED"] = "minimax/minimax-m1:extended"; 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"; @@ -179883,14 +179878,12 @@ var E_OPENROUTER_MODEL_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_11B_VISION_INSTRUCT_FREE"] = "meta-llama/llama-3.2-11b-vision-instruct:free"; - E_OPENROUTER_MODEL_FREE["MODEL_FREE_META_LLAMA_LLAMA_3_2_1B_INSTRUCT_FREE"] = "meta-llama/llama-3.2-1b-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_META_LLAMA_LLAMA_3_1_8B_INSTRUCT_FREE"] = "meta-llama/llama-3.1-8b-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 @@ -199415,9 +199408,10 @@ const tools_load = async (options) => { /* harmony export */ __webpack_require__.d(__webpack_exports__, { /* harmony export */ IA: () => (/* binding */ E_Mode), /* harmony export */ IO: () => (/* binding */ OptionsSchema), -/* harmony export */ gK: () => (/* binding */ types) +/* harmony export */ gK: () => (/* binding */ types), +/* harmony export */ jo: () => (/* binding */ schemas) /* harmony export */ }); -/* unused harmony exports get_var, HOME, PREFERENCES_DEFAULT, E_Filters, E_RouterTypeSchema, EType, E_AppendMode, E_WrapMode, E_GlobExtension, schemas */ +/* unused harmony exports get_var, HOME, PREFERENCES_DEFAULT, E_Filters, E_RouterTypeSchema, EType, E_AppendMode, E_WrapMode, E_GlobExtension */ /* harmony import */ var zod__WEBPACK_IMPORTED_MODULE_14__ = __webpack_require__(14476); /* harmony import */ var node_path__WEBPACK_IMPORTED_MODULE_0__ = __webpack_require__(76760); /* harmony import */ var chalk__WEBPACK_IMPORTED_MODULE_1__ = __webpack_require__(55248); @@ -231023,6 +231017,7 @@ main_yargs(main_hideBin(process.argv)) .command('init', 'Initialize KBot configuration', (yargs) => (0,main_dist/* toYargs */.aH)(yargs, (0,main_zod_schema/* OptionsSchema */.IO)(), main_yargOptions), main_init) .command('modify [prompt]', 'Modify an existing project', (yargs) => (0,main_dist/* toYargs */.aH)(yargs, (0,main_zod_schema/* OptionsSchema */.IO)(), main_yargOptions), main_modify) .command('types', 'Generate types', (yargs) => { }, (argv) => (0,main_zod_schema/* types */.gK)()) + .command('schemas', 'Generate schemas', (yargs) => { }, (argv) => (0,main_zod_schema/* schemas */.jo)()) .command('build', 'Build kbot essentials', (yargs) => { }, (argv) => main_build()) .command('fetch', "Fetch models, to $HOME/.kbot/", (yargs) => { }, (argv) => main_fetch()) .command('help-md', 'Generate markdown help', (yargs) => { }, main_commands_help) @@ -231031,7 +231026,7 @@ main_yargs(main_hideBin(process.argv)) .help() //.wrap(yargs.terminalWidth() - 20) .parse(); -//# 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+//# 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})(); /******/ })() diff --git a/packages/kbot/dist/package-lock.json b/packages/kbot/dist/package-lock.json index 55d1f979..c3bc384b 100644 --- a/packages/kbot/dist/package-lock.json +++ b/packages/kbot/dist/package-lock.json @@ -1,12 +1,12 @@ { "name": "@plastichub/kbot", - "version": "1.1.44", + "version": "1.1.45", "lockfileVersion": 3, "requires": true, "packages": { "": { "name": "@plastichub/kbot", - "version": "1.1.44", + "version": "1.1.45", "license": "ISC", "dependencies": { "node-emoji": "^2.2.0" diff --git a/packages/kbot/dist/package.json b/packages/kbot/dist/package.json index 191bcab0..aab88b76 100644 --- a/packages/kbot/dist/package.json +++ b/packages/kbot/dist/package.json @@ -1,6 +1,6 @@ { "name": "@plastichub/kbot", - "version": "1.1.44", + "version": "1.1.45", "main": "main_node.js", "author": "", "license": "ISC", diff --git a/packages/kbot/extensions/gui/package.json b/packages/kbot/extensions/gui/package.json index bd457967..f1c99564 100644 --- a/packages/kbot/extensions/gui/package.json +++ b/packages/kbot/extensions/gui/package.json @@ -60,10 +60,6 @@ "cross-env": "^7.0.3", "css-loader": "^7.1.2", "electron": "^31.2.1", - "eslint": "^9.7.0", - "eslint-import-resolver-alias": "^1.1.2", - "eslint-plugin-import": "^2.29.1", - "eslint-plugin-react": "^7.34.4", "file-loader": "^6.2.0", "fork-ts-checker-webpack-plugin": "^9.0.2", "json-loader": "^0.5.7", diff --git a/packages/kbot/extensions/gui/src/renderer/components/Application.tsx b/packages/kbot/extensions/gui/src/renderer/components/Application.tsx index 0e323c3a..e2bd6cbc 100644 --- a/packages/kbot/extensions/gui/src/renderer/components/Application.tsx +++ b/packages/kbot/extensions/gui/src/renderer/components/Application.tsx @@ -1,12 +1,5 @@ -import * as path from 'path'; -import * as fs from 'fs'; -import { sync as read } from '@plastichub/fs/read'; -import { sync as write } from '@plastichub/fs/write'; -import { sync as mkdir } from '@plastichub/fs/dir'; -import { sync as exists } from '@plastichub/fs/exists'; import React, { useEffect, useState } from 'react'; import '@styles/app.scss'; -import icons from '@components/icons'; import Form from '@rjsf/mui' import { RJSFSchema } from '@rjsf/utils'; diff --git a/packages/kbot/src/models/cache/openai-models.ts b/packages/kbot/src/models/cache/openai-models.ts index 6984f11d..2e5de895 100644 --- a/packages/kbot/src/models/cache/openai-models.ts +++ b/packages/kbot/src/models/cache/openai-models.ts @@ -52,8 +52,6 @@ export enum E_OPENAI_MODEL { MODEL_O3_MINI = "o3-mini", MODEL_O3_MINI_2025_01_31 = "o3-mini-2025-01-31", MODEL_GPT_4O_2024_11_20 = "gpt-4o-2024-11-20", - MODEL_GPT_4_5_PREVIEW = "gpt-4.5-preview", - MODEL_GPT_4_5_PREVIEW_2025_02_27 = "gpt-4.5-preview-2025-02-27", MODEL_GPT_4O_SEARCH_PREVIEW_2025_03_11 = "gpt-4o-search-preview-2025-03-11", MODEL_GPT_4O_SEARCH_PREVIEW = "gpt-4o-search-preview", MODEL_GPT_4O_MINI_SEARCH_PREVIEW_2025_03_11 = "gpt-4o-mini-search-preview-2025-03-11", diff --git a/packages/kbot/src/models/cache/openrouter-models-free.ts b/packages/kbot/src/models/cache/openrouter-models-free.ts index a7a1e898..3c5be551 100644 --- a/packages/kbot/src/models/cache/openrouter-models-free.ts +++ b/packages/kbot/src/models/cache/openrouter-models-free.ts @@ -1,12 +1,17 @@ export enum E_OPENROUTER_MODEL_FREE { - MODEL_FREE_OPENROUTER_CYPHER_ALPHA_FREE = "openrouter/cypher-alpha: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_SARVAMAI_SARVAM_M_FREE = "sarvamai/sarvam-m:free", - MODEL_FREE_MISTRALAI_DEVSTRAL_SMALL_FREE = "mistralai/devstral-small: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_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", @@ -20,10 +25,7 @@ export enum E_OPENROUTER_MODEL_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_NVIDIA_LLAMA_3_3_NEMOTRON_SUPER_49B_V1_FREE = "nvidia/llama-3.3-nemotron-super-49b-v1:free", MODEL_FREE_NVIDIA_LLAMA_3_1_NEMOTRON_ULTRA_253B_V1_FREE = "nvidia/llama-3.1-nemotron-ultra-253b-v1: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_DEEPSEEK_DEEPSEEK_V3_BASE_FREE = "deepseek/deepseek-v3-base:free", MODEL_FREE_GOOGLE_GEMINI_2_5_PRO_EXP_03_25 = "google/gemini-2.5-pro-exp-03-25", MODEL_FREE_QWEN_QWEN2_5_VL_32B_INSTRUCT_FREE = "qwen/qwen2.5-vl-32b-instruct:free", @@ -47,8 +49,10 @@ export enum E_OPENROUTER_MODEL_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_META_LLAMA_LLAMA_3_2_11B_VISION_INSTRUCT_FREE = "meta-llama/llama-3.2-11b-vision-instruct:free", MODEL_FREE_QWEN_QWEN_2_5_72B_INSTRUCT_FREE = "qwen/qwen-2.5-72b-instruct: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/src/models/cache/openrouter-models.ts b/packages/kbot/src/models/cache/openrouter-models.ts index a441828f..76db5f97 100644 --- a/packages/kbot/src/models/cache/openrouter-models.ts +++ b/packages/kbot/src/models/cache/openrouter-models.ts @@ -1,5 +1,18 @@ export enum E_OPENROUTER_MODEL { - MODEL_OPENROUTER_CYPHER_ALPHA_FREE = "openrouter/cypher-alpha:free", + MODEL_SWITCHPOINT_ROUTER = "switchpoint/router", + MODEL_MOONSHOTAI_KIMI_K2_FREE = "moonshotai/kimi-k2:free", + MODEL_MOONSHOTAI_KIMI_K2 = "moonshotai/kimi-k2", + MODEL_THUDM_GLM_4_1V_9B_THINKING = "thudm/glm-4.1v-9b-thinking", + MODEL_MISTRALAI_DEVSTRAL_MEDIUM = "mistralai/devstral-medium", + MODEL_MISTRALAI_DEVSTRAL_SMALL = "mistralai/devstral-small", + 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_MORPH_MORPH_V3_LARGE = "morph/morph-v3-large", + MODEL_MORPH_MORPH_V3_FAST = "morph/morph-v3-fast", 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", @@ -24,15 +37,14 @@ export enum E_OPENROUTER_MODEL { MODEL_DEEPSEEK_DEEPSEEK_R1_0528_FREE = "deepseek/deepseek-r1-0528:free", MODEL_DEEPSEEK_DEEPSEEK_R1_0528 = "deepseek/deepseek-r1-0528", MODEL_SARVAMAI_SARVAM_M_FREE = "sarvamai/sarvam-m:free", + MODEL_SARVAMAI_SARVAM_M = "sarvamai/sarvam-m", MODEL_THEDRUMMER_VALKYRIE_49B_V1 = "thedrummer/valkyrie-49b-v1", MODEL_ANTHROPIC_CLAUDE_OPUS_4 = "anthropic/claude-opus-4", MODEL_ANTHROPIC_CLAUDE_SONNET_4 = "anthropic/claude-sonnet-4", - MODEL_MISTRALAI_DEVSTRAL_SMALL_FREE = "mistralai/devstral-small:free", - MODEL_MISTRALAI_DEVSTRAL_SMALL = "mistralai/devstral-small", + 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_GOOGLE_GEMINI_2_5_FLASH_PREVIEW_05_20 = "google/gemini-2.5-flash-preview-05-20", - MODEL_GOOGLE_GEMINI_2_5_FLASH_PREVIEW_05_20_THINKING = "google/gemini-2.5-flash-preview-05-20:thinking", MODEL_OPENAI_CODEX_MINI = "openai/codex-mini", 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", @@ -45,6 +57,7 @@ export enum E_OPENROUTER_MODEL { MODEL_ARCEE_AI_ARCEE_BLITZ = "arcee-ai/arcee-blitz", MODEL_MICROSOFT_PHI_4_REASONING_PLUS = "microsoft/phi-4-reasoning-plus", MODEL_INCEPTION_MERCURY_CODER = "inception/mercury-coder", + MODEL_QWEN_QWEN3_4B_FREE = "qwen/qwen3-4b:free", MODEL_OPENGVLAB_INTERNVL3_14B = "opengvlab/internvl3-14b", MODEL_DEEPSEEK_DEEPSEEK_PROVER_V2 = "deepseek/deepseek-prover-v2", MODEL_META_LLAMA_LLAMA_GUARD_4_12B = "meta-llama/llama-guard-4-12b", @@ -63,8 +76,6 @@ export enum E_OPENROUTER_MODEL { MODEL_THUDM_GLM_Z1_32B_FREE = "thudm/glm-z1-32b:free", MODEL_THUDM_GLM_4_32B_FREE = "thudm/glm-4-32b:free", MODEL_THUDM_GLM_4_32B = "thudm/glm-4-32b", - MODEL_GOOGLE_GEMINI_2_5_FLASH_PREVIEW = "google/gemini-2.5-flash-preview", - MODEL_GOOGLE_GEMINI_2_5_FLASH_PREVIEW_THINKING = "google/gemini-2.5-flash-preview:thinking", MODEL_OPENAI_O4_MINI_HIGH = "openai/o4-mini-high", MODEL_OPENAI_O3 = "openai/o3", MODEL_OPENAI_O4_MINI = "openai/o4-mini", @@ -76,18 +87,15 @@ export enum E_OPENROUTER_MODEL { 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_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_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_3_NEMOTRON_SUPER_49B_V1_FREE = "nvidia/llama-3.3-nemotron-super-49b-v1:free", MODEL_NVIDIA_LLAMA_3_3_NEMOTRON_SUPER_49B_V1 = "nvidia/llama-3.3-nemotron-super-49b-v1", MODEL_NVIDIA_LLAMA_3_1_NEMOTRON_ULTRA_253B_V1_FREE = "nvidia/llama-3.1-nemotron-ultra-253b-v1:free", 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_ALL_HANDS_OPENHANDS_LM_32B_V0_1 = "all-hands/openhands-lm-32b-v0.1", MODEL_DEEPSEEK_DEEPSEEK_V3_BASE_FREE = "deepseek/deepseek-v3-base:free", MODEL_SCB10X_LLAMA3_1_TYPHOON2_70B_INSTRUCT = "scb10x/llama3.1-typhoon2-70b-instruct", MODEL_GOOGLE_GEMINI_2_5_PRO_EXP_03_25 = "google/gemini-2.5-pro-exp-03-25", @@ -109,6 +117,7 @@ export enum E_OPENROUTER_MODEL { MODEL_OPENAI_GPT_4O_MINI_SEARCH_PREVIEW = "openai/gpt-4o-mini-search-preview", MODEL_OPENAI_GPT_4O_SEARCH_PREVIEW = "openai/gpt-4o-search-preview", MODEL_REKAAI_REKA_FLASH_3_FREE = "rekaai/reka-flash-3:free", + MODEL_REKAAI_REKA_FLASH_3 = "rekaai/reka-flash-3", 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", @@ -120,7 +129,6 @@ export enum E_OPENROUTER_MODEL { 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_OPENAI_GPT_4_5_PREVIEW = "openai/gpt-4.5-preview", 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", @@ -128,6 +136,7 @@ export enum E_OPENROUTER_MODEL { MODEL_PERPLEXITY_R1_1776 = "perplexity/r1-1776", 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_META_LLAMA_LLAMA_GUARD_3_8B = "meta-llama/llama-guard-3-8b", MODEL_OPENAI_O3_MINI_HIGH = "openai/o3-mini-high", @@ -186,38 +195,37 @@ export enum E_OPENROUTER_MODEL { 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_EVA_UNIT_01_EVA_QWEN_2_5_32B = "eva-unit-01/eva-qwen-2.5-32b", MODEL_THEDRUMMER_UNSLOPNEMO_12B = "thedrummer/unslopnemo-12b", MODEL_ANTHROPIC_CLAUDE_3_5_HAIKU_BETA = "anthropic/claude-3.5-haiku:beta", MODEL_ANTHROPIC_CLAUDE_3_5_HAIKU = "anthropic/claude-3.5-haiku", MODEL_ANTHROPIC_CLAUDE_3_5_HAIKU_20241022_BETA = "anthropic/claude-3.5-haiku-20241022:beta", MODEL_ANTHROPIC_CLAUDE_3_5_HAIKU_20241022 = "anthropic/claude-3.5-haiku-20241022", - MODEL_NEVERSLEEP_LLAMA_3_1_LUMIMAID_70B = "neversleep/llama-3.1-lumimaid-70b", MODEL_ANTHRACITE_ORG_MAGNUM_V4_72B = "anthracite-org/magnum-v4-72b", MODEL_ANTHROPIC_CLAUDE_3_5_SONNET_BETA = "anthropic/claude-3.5-sonnet:beta", 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_MISTRALAI_MINISTRAL_8B = "mistralai/ministral-8b", 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_THEDRUMMER_ROCINANTE_12B = "thedrummer/rocinante-12b", - MODEL_ANTHRACITE_ORG_MAGNUM_V2_72B = "anthracite-org/magnum-v2-72b", MODEL_LIQUID_LFM_40B = "liquid/lfm-40b", + 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_FREE = "meta-llama/llama-3.2-11b-vision-instruct:free", MODEL_META_LLAMA_LLAMA_3_2_11B_VISION_INSTRUCT = "meta-llama/llama-3.2-11b-vision-instruct", + MODEL_META_LLAMA_LLAMA_3_2_90B_VISION_INSTRUCT = "meta-llama/llama-3.2-90b-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_PREVIEW = "openai/o1-preview", + MODEL_OPENAI_O1_MINI_2024_09_12 = "openai/o1-mini-2024-09-12", MODEL_OPENAI_O1_PREVIEW_2024_09_12 = "openai/o1-preview-2024-09-12", 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", @@ -227,20 +235,19 @@ export enum E_OPENROUTER_MODEL { MODEL_NOUSRESEARCH_HERMES_3_LLAMA_3_1_70B = "nousresearch/hermes-3-llama-3.1-70b", 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", MODEL_AETHERWIING_MN_STARCANNON_12B = "aetherwiing/mn-starcannon-12b", + MODEL_SAO10K_L3_LUNARIS_8B = "sao10k/l3-lunaris-8b", MODEL_OPENAI_GPT_4O_2024_08_06 = "openai/gpt-4o-2024-08-06", MODEL_META_LLAMA_LLAMA_3_1_405B = "meta-llama/llama-3.1-405b", MODEL_NOTHINGIISREAL_MN_CELESTE_12B = "nothingiisreal/mn-celeste-12b", - MODEL_PERPLEXITY_LLAMA_3_1_SONAR_SMALL_128K_ONLINE = "perplexity/llama-3.1-sonar-small-128k-online", - MODEL_PERPLEXITY_LLAMA_3_1_SONAR_LARGE_128K_ONLINE = "perplexity/llama-3.1-sonar-large-128k-online", MODEL_META_LLAMA_LLAMA_3_1_8B_INSTRUCT = "meta-llama/llama-3.1-8b-instruct", - 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_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_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_ALPINDALE_MAGNUM_72B = "alpindale/magnum-72b", MODEL_GOOGLE_GEMMA_2_9B_IT_FREE = "google/gemma-2-9b-it:free", @@ -251,19 +258,18 @@ export enum E_OPENROUTER_MODEL { MODEL_SAO10K_L3_EURYALE_70B = "sao10k/l3-euryale-70b", MODEL_COGNITIVECOMPUTATIONS_DOLPHIN_MIXTRAL_8X22B = "cognitivecomputations/dolphin-mixtral-8x22b", MODEL_QWEN_QWEN_2_72B_INSTRUCT = "qwen/qwen-2-72b-instruct", + MODEL_MISTRALAI_MISTRAL_7B_INSTRUCT_V0_3 = "mistralai/mistral-7b-instruct-v0.3", MODEL_MISTRALAI_MISTRAL_7B_INSTRUCT_FREE = "mistralai/mistral-7b-instruct:free", MODEL_MISTRALAI_MISTRAL_7B_INSTRUCT = "mistralai/mistral-7b-instruct", MODEL_NOUSRESEARCH_HERMES_2_PRO_LLAMA_3_8B = "nousresearch/hermes-2-pro-llama-3-8b", - 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_2024_05_13 = "openai/gpt-4o-2024-05-13", + MODEL_META_LLAMA_LLAMA_GUARD_2_8B = "meta-llama/llama-guard-2-8b", 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_NEVERSLEEP_LLAMA_3_LUMIMAID_8B = "neversleep/llama-3-lumimaid-8b", MODEL_SAO10K_FIMBULVETR_11B_V2 = "sao10k/fimbulvetr-11b-v2", MODEL_META_LLAMA_LLAMA_3_8B_INSTRUCT = "meta-llama/llama-3-8b-instruct", MODEL_META_LLAMA_LLAMA_3_70B_INSTRUCT = "meta-llama/llama-3-70b-instruct", @@ -274,8 +280,8 @@ export enum E_OPENROUTER_MODEL { MODEL_COHERE_COMMAND_R_PLUS = "cohere/command-r-plus", MODEL_COHERE_COMMAND_R_PLUS_04_2024 = "cohere/command-r-plus-04-2024", MODEL_SOPHOSYMPATHEIA_MIDNIGHT_ROSE_70B = "sophosympatheia/midnight-rose-70b", - MODEL_COHERE_COMMAND = "cohere/command", MODEL_COHERE_COMMAND_R = "cohere/command-r", + MODEL_COHERE_COMMAND = "cohere/command", MODEL_ANTHROPIC_CLAUDE_3_HAIKU_BETA = "anthropic/claude-3-haiku:beta", MODEL_ANTHROPIC_CLAUDE_3_HAIKU = "anthropic/claude-3-haiku", MODEL_ANTHROPIC_CLAUDE_3_OPUS_BETA = "anthropic/claude-3-opus:beta", @@ -284,11 +290,11 @@ export enum E_OPENROUTER_MODEL { MODEL_ANTHROPIC_CLAUDE_3_SONNET = "anthropic/claude-3-sonnet", 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_OPENAI_GPT_3_5_TURBO_0613 = "openai/gpt-3.5-turbo-0613", MODEL_NOUSRESEARCH_NOUS_HERMES_2_MIXTRAL_8X7B_DPO = "nousresearch/nous-hermes-2-mixtral-8x7b-dpo", - MODEL_MISTRALAI_MISTRAL_SMALL = "mistralai/mistral-small", MODEL_MISTRALAI_MISTRAL_TINY = "mistralai/mistral-tiny", + MODEL_MISTRALAI_MISTRAL_SMALL = "mistralai/mistral-small", 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", @@ -296,12 +302,12 @@ export enum E_OPENROUTER_MODEL { MODEL_ANTHROPIC_CLAUDE_2_1 = "anthropic/claude-2.1", MODEL_ANTHROPIC_CLAUDE_2_BETA = "anthropic/claude-2:beta", MODEL_ANTHROPIC_CLAUDE_2 = "anthropic/claude-2", - MODEL_UNDI95_TOPPY_M_7B = "undi95/toppy-m-7b", MODEL_ALPINDALE_GOLIATH_120B = "alpindale/goliath-120b", + MODEL_UNDI95_TOPPY_M_7B = "undi95/toppy-m-7b", MODEL_OPENROUTER_AUTO = "openrouter/auto", MODEL_OPENAI_GPT_4_1106_PREVIEW = "openai/gpt-4-1106-preview", - MODEL_OPENAI_GPT_3_5_TURBO_INSTRUCT = "openai/gpt-3.5-turbo-instruct", MODEL_MISTRALAI_MISTRAL_7B_INSTRUCT_V0_1 = "mistralai/mistral-7b-instruct-v0.1", + MODEL_OPENAI_GPT_3_5_TURBO_INSTRUCT = "openai/gpt-3.5-turbo-instruct", MODEL_PYGMALIONAI_MYTHALION_13B = "pygmalionai/mythalion-13b", MODEL_OPENAI_GPT_3_5_TURBO_16K = "openai/gpt-3.5-turbo-16k", MODEL_MANCER_WEAVER = "mancer/weaver", @@ -310,5 +316,6 @@ export enum E_OPENROUTER_MODEL { MODEL_UNDI95_REMM_SLERP_L2_13B = "undi95/remm-slerp-l2-13b", MODEL_GRYPHE_MYTHOMAX_L2_13B = "gryphe/mythomax-l2-13b", MODEL_OPENAI_GPT_4 = "openai/gpt-4", + MODEL_OPENAI_GPT_3_5_TURBO = "openai/gpt-3.5-turbo", MODEL_OPENAI_GPT_4_0314 = "openai/gpt-4-0314" } \ No newline at end of file