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feat: upgrade MiniMax default model to M2.7 (#3865)

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Add MiniMax-M2.7 and M2.7-highspeed to model selection lists. Set M2.7 as the new default for MiniMax, Novita, and Ollama cloud providers. Retain all previous models (M2.5, M2.1, M2) as alternatives.
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Octopus 2026-03-19 21:33:29 -05:00 committed by GitHub
parent 128b33e717
commit 64ecb76773
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1 changed files with 32 additions and 13 deletions
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45
src/onboard/wizard.rs
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@ -783,10 +783,15 @@ fn allows_unauthenticated_model_fetch(provider_name: &str) -> bool {
}
/// Pick a sensible default model for the given provider.
const MINIMAX_ONBOARD_MODELS: [(&str, &str); 5] = [
("MiniMax-M2.5", "MiniMax M2.5 (latest, recommended)"),
const MINIMAX_ONBOARD_MODELS: [(&str, &str); 7] = [
(
"MiniMax-M2.7",
"MiniMax M2.7 (latest flagship, recommended)",
),
("MiniMax-M2.7-highspeed", "MiniMax M2.7 High-Speed (faster)"),
("MiniMax-M2.5", "MiniMax M2.5 (stable)"),
("MiniMax-M2.5-highspeed", "MiniMax M2.5 High-Speed (faster)"),
("MiniMax-M2.1", "MiniMax M2.1 (stable)"),
("MiniMax-M2.1", "MiniMax M2.1 (previous gen)"),
("MiniMax-M2.1-highspeed", "MiniMax M2.1 High-Speed (faster)"),
("MiniMax-M2", "MiniMax M2 (legacy)"),
];
@ -803,12 +808,12 @@ fn default_model_for_provider(provider: &str) -> String {
"xai" => "grok-4-1-fast-reasoning".into(),
"perplexity" => "sonar-pro".into(),
"fireworks" => "accounts/fireworks/models/llama-v3p3-70b-instruct".into(),
"novita" => "minimax/minimax-m2.5".into(),
"novita" => "minimax/minimax-m2.7".into(),
"together-ai" => "meta-llama/Llama-3.3-70B-Instruct-Turbo".into(),
"cohere" => "command-a-03-2025".into(),
"moonshot" => "kimi-k2.5".into(),
"glm" | "zai" => "glm-5".into(),
"minimax" => "MiniMax-M2.5".into(),
"minimax" => "MiniMax-M2.7".into(),
"qwen" => "qwen-plus".into(),
"qwen-code" => "qwen3-coder-plus".into(),
"ollama" => "llama3.2".into(),
@ -997,10 +1002,16 @@ fn curated_models_for_provider(provider_name: &str) -> Vec<(String, String)> {
"Mixtral 8x22B".to_string(),
),
],
"novita" => vec![(
"minimax/minimax-m2.5".to_string(),
"MiniMax M2.5".to_string(),
)],
"novita" => vec![
(
"minimax/minimax-m2.7".to_string(),
"MiniMax M2.7 (latest flagship)".to_string(),
),
(
"minimax/minimax-m2.5".to_string(),
"MiniMax M2.5".to_string(),
),
],
"together-ai" => vec![
(
"meta-llama/Llama-3.3-70B-Instruct-Turbo".to_string(),
@ -1065,9 +1076,17 @@ fn curated_models_for_provider(provider_name: &str) -> Vec<(String, String)> {
),
],
"minimax" => vec![
(
"MiniMax-M2.7".to_string(),
"MiniMax M2.7 (latest flagship)".to_string(),
),
(
"MiniMax-M2.7-highspeed".to_string(),
"MiniMax M2.7 High-Speed (fast)".to_string(),
),
(
"MiniMax-M2.5".to_string(),
"MiniMax M2.5 (latest flagship)".to_string(),
"MiniMax M2.5 (stable)".to_string(),
),
(
"MiniMax-M2.5-highspeed".to_string(),
@ -1075,7 +1094,7 @@ fn curated_models_for_provider(provider_name: &str) -> Vec<(String, String)> {
),
(
"MiniMax-M2.1".to_string(),
"MiniMax M2.1 (strong coding/reasoning)".to_string(),
"MiniMax M2.1 (previous gen)".to_string(),
),
],
"qwen" => vec![
@ -1621,7 +1640,7 @@ fn fetch_live_models_for_provider(
"qwen3-coder-next:cloud".to_string(),
"qwen3-coder:480b:cloud".to_string(),
"kimi-k2.5:cloud".to_string(),
"minimax-m2.5:cloud".to_string(),
"minimax-m2.7:cloud".to_string(),
"deepseek-v3.1:671b:cloud".to_string(),
]
} else {
@ -6651,7 +6670,7 @@ mod tests {
assert_eq!(default_model_for_provider("qwen-intl"), "qwen-plus");
assert_eq!(default_model_for_provider("qwen-code"), "qwen3-coder-plus");
assert_eq!(default_model_for_provider("glm-cn"), "glm-5");
assert_eq!(default_model_for_provider("minimax-cn"), "MiniMax-M2.5");
assert_eq!(default_model_for_provider("minimax-cn"), "MiniMax-M2.7");
assert_eq!(default_model_for_provider("zai-cn"), "glm-5");
assert_eq!(default_model_for_provider("gemini"), "gemini-2.5-pro");
assert_eq!(default_model_for_provider("google"), "gemini-2.5-pro");