Request a pilot
‹ PublicAI Index

The LLM benchmark aggregator.

Codestral 25.01

Mistral

Strongest in Agentic coding (#142 of 169, on 1 of its 5 boards), weakest in Coding (#144 of 176). Above par in 0 of 2 scopes. Among the models it meets almost everywhere, it finishes behind Claude Opus 5.5 and Claude Opus 5 and ahead of Openhands Lm 32B V0.1 and Qwen3 Max.

§ 1 · Profile

What it is good at

Bars run from 50 — the average of the models each source lists — so right of the line is above par. The middle column is the gap to whoever leads that scope.

Coding42.8#144/176
Agentic coding42.2#142/169

§ 2 · Head to head

What it beats, and what beats it

The same models turn up scope after scope. Counted once: where both were placed, who finished higher. Bars run right for Codestral 25.01, left for the other.

Grok 4.1 Fastwon 2 · lost 0
GPT-4o Miniwon 2 · lost 0
Claude Haiku 4.5won 2 · lost 0
Ling 3.0 Flash Finwon 2 · lost 0
Grok 4.3won 2 · lost 0
Mercury 2.5won 2 · lost 0
Command Awon 2 · lost 0
Mistral Medium 3.5won 2 · lost 0
Mistral Large 3won 2 · lost 0
Laguna XS.2won 2 · lost 0
Grok 4 Fastwon 2 · lost 0
Grok 4.20won 2 · lost 0
Laguna M.1won 2 · lost 0
Gemma 4 31Bwon 2 · lost 0
Gemma 3 27B Itwon 2 · lost 0
Gemini 3.1 Flash Litewon 2 · lost 0
Qwen3.6 27Bwon 2 · lost 0
GPT OSS 120Bwon 2 · lost 0
Ling 3.0 Flashwon 2 · lost 0
Kimi K2.5won 2 · lost 0
GPT-5 Miniwon 2 · lost 0
GLM-4.6won 2 · lost 0
GPT-4.1 Nanowon 2 · lost 0
Qwen3 Maxwon 2 · lost 0
Openhands Lm 32B V0.1won 2 · lost 0
GPT-4owon 1 · lost 1
Qwen3.6 Pluswon 1 · lost 1
MiniMax M2.7won 1 · lost 1
Command A Qualitywon 0 · lost 2
SWE-1.6 Fastwon 0 · lost 2
Yi Lightningwon 0 · lost 2
Grok Build 0.1won 0 · lost 2
Gemini 3 Flashwon 0 · lost 2
Inklingwon 0 · lost 2
GPT-5.4 Nanowon 0 · lost 2
GPT 5.1 Codexwon 0 · lost 2
Claude Opus 4.5won 0 · lost 2
Gemini 3.5 Flash Litewon 0 · lost 2
DeepSeek V2.5won 0 · lost 2
Qwen3.7 Maxwon 0 · lost 2
GPT-5.4 Miniwon 0 · lost 2
Gemini 3.1 Prowon 0 · lost 2
QwQ 32Bwon 0 · lost 2
Qwen Maxwon 0 · lost 2
Gemini 2.0 Flashwon 0 · lost 2
Kimi K2 Thinkingwon 0 · lost 2
Qwen 3.5 Pluswon 0 · lost 2
Nemotron 3 Nano 4Bwon 0 · lost 2
MiniMax M3won 0 · lost 2
Gemma 4 E4Bwon 0 · lost 2
G9v3 3Bwon 0 · lost 2
GPT 5.1 Codex Maxwon 0 · lost 2
Claude Sonnet 4.5won 0 · lost 2
DeepSeek V3won 0 · lost 2
Qwen3.7 Pluswon 0 · lost 2
MiniMax M2.5won 0 · lost 2
GPT-5.1won 0 · lost 2
Mimo V2.5won 0 · lost 2
Inkling Smallwon 0 · lost 2
Devstral 2won 0 · lost 2
Nemotron 3.5 Super VLwon 0 · lost 2
GLM-5won 0 · lost 2
K2 Horizon 7Bwon 0 · lost 2
Gemini 3 Prowon 0 · lost 2
Claude 3.5 Haikuwon 0 · lost 2
Qwen3.5 Flashwon 0 · lost 2
Mimo V2.5 Prowon 0 · lost 2
Claude 3.5 Sonnetwon 0 · lost 2
Granite 4.2 3Bwon 0 · lost 2
GPT-4.1 Miniwon 0 · lost 2
Qwen3.5 4Bwon 0 · lost 2
O1 Miniwon 0 · lost 2
Kimi K2.6won 0 · lost 2
GPT-5.2 Codexwon 0 · lost 2
GLM-5.1won 0 · lost 2
Gemini 2.0 Prowon 0 · lost 2
DeepSeek V3.2won 0 · lost 2
Kimi K2.7 Codewon 0 · lost 2
Claude Sonnet 4.6won 0 · lost 2
GLM-4.7won 0 · lost 2
Qwen3.8 Max 0902won 0 · lost 2
Muse Spark Openwon 0 · lost 2
Gemini Exp 1206won 0 · lost 2
Granite 4.2 8Bwon 0 · lost 2
Gemma 4 12Bwon 0 · lost 2
K2 Horizon 32Bwon 0 · lost 2
Qwen3.5 9Bwon 0 · lost 2
Qwen3 32Bwon 0 · lost 2
Gemini 2.5 Prowon 0 · lost 2
Granite 4.2 30Bwon 0 · lost 2
G9v3 39A5Bwon 0 · lost 2
Gemini 3.5 Flashwon 0 · lost 2
K2 Horizon 3.7Bwon 0 · lost 2
Qwen3.6 Maxwon 0 · lost 2
Gemini 3.6 Flashwon 0 · lost 2
Qwen3.6 35B A3Bwon 0 · lost 2
DeepSeek V4won 0 · lost 2
GPT-4.5won 0 · lost 2
ChatGPT-4owon 0 · lost 2
Ox Alphawon 0 · lost 2
GPT-5.2won 0 · lost 2
MiniMax M2.1won 0 · lost 2
Claude Opus 4.6won 0 · lost 2
Mistral Large 4won 0 · lost 2
Nemotron 3.5 30B-A3Bwon 0 · lost 2
Muse Sparkwon 0 · lost 2
Muse Glimmer-30Bwon 0 · lost 2
Grok 4won 0 · lost 2
GLM-5.3 Flashwon 0 · lost 2
Composer 2.5won 0 · lost 2
GPT-4.1won 0 · lost 2
GPT-5won 0 · lost 2
Beam 1.0won 0 · lost 2
Optimus Alphawon 0 · lost 2
Grok 3won 0 · lost 2
Quasar Alphawon 0 · lost 2
Qwen3.8 Maxwon 0 · lost 2
K2 Horizon 375B A23Bwon 0 · lost 2
Gemini 3.7 Flashwon 0 · lost 2
Claude Sonnet 4won 0 · lost 2
GPT-5.3 Codexwon 0 · lost 2
Qwen3.8 Flashwon 0 · lost 2
Gemini 2.5 Flashwon 0 · lost 2
Grok 3 Miniwon 0 · lost 2
GPT-6 Lunawon 0 · lost 2
Kimi K2won 0 · lost 2
GPT-5.4won 0 · lost 2
Gemini 3.8 Flashwon 0 · lost 2
GPT-5.6 Lunawon 0 · lost 2
Kimi K3won 0 · lost 2
GLM-5.2won 0 · lost 2
O1won 0 · lost 2
Claude Sonnet 5won 0 · lost 2
Qwen3.8 27Bwon 0 · lost 2
DeepSeek V4 Flashwon 0 · lost 2
Claude 3.7 Sonnetwon 0 · lost 2
Claude Opus 4.7won 0 · lost 2
Ember 1won 0 · lost 2
Claude Opus 4won 0 · lost 2
Step 5won 0 · lost 2
Claude Opus 4.8won 0 · lost 2
Qwen3.8 Flash Nextwon 0 · lost 2
O3 Miniwon 0 · lost 2
Muse Spark 1.1won 0 · lost 2
Grok 4.5won 0 · lost 2
Muse Spark 1.2won 0 · lost 2
Mimo V2.6 Flashwon 0 · lost 2
GPT-5.5won 0 · lost 2
Grok 4.7won 0 · lost 2
Mimo V2.6 Prowon 0 · lost 2
Hy4won 0 · lost 2
Claude Haiku 5.5won 0 · lost 2
GPT-5.6 Terrawon 0 · lost 2
O3 + gpt-4.1won 0 · lost 2
Grok 4.6won 0 · lost 2
Muse Spark 1.3won 0 · lost 2
DeepSeek R1won 0 · lost 2
O3 Prowon 0 · lost 2
DeepSeek V4 Prowon 0 · lost 2
GLM-5.3won 0 · lost 2
Claude Sonnet 5.5won 0 · lost 2
GPT-6 Solwon 0 · lost 2
O4 Miniwon 0 · lost 2
GPT-5.6 Solwon 0 · lost 2
O3won 0 · lost 2
Muse Wonder Fullwon 0 · lost 2
Muse Wonderwon 0 · lost 2
GPT-6.1 Solwon 0 · lost 2
Gemini 4 Argonwon 0 · lost 2
GPT-6 Astrawon 0 · lost 2
DeepSeek V4.1 Flashwon 0 · lost 2
Claude Fable 5won 0 · lost 2
Claude Fable 5.1won 0 · lost 2
Claude Opus 5won 0 · lost 2
Claude Opus 5.5won 0 · lost 2

§ 3 · Sources

Where the numbers come from

1 publication, 1 figures. Every one links to the page it was read from.

Aider polyglot ↗1 measureread 2026-10-19
Aider polyglot 11.1%

Badge

PublicAI Index badge for Codestral 25.01[![PublicAI Index](https://publicai.io/model-index/badge?model=codestral-25-01)](https://publicai.io/model-index/m/codestral-25-01)