Codestral Instruct on MATH-500: score, rank and what it means
Codestral Instruct scores 78.1 on MATH-500, placing it #256 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.
Score distribution
The chart shows the top 10 models on MATH-500, with Codestral Instruct highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|---|
| 1 | GPT-5.2 Max | OpenAI | 1000000 | $21.39 | 89.2 |
| 2 | GPT-5.1 Reasoning | OpenAI | 400000 | $20.27 | 88.3 |
| 3 | GPT-5.1 Pro | OpenAI | 200000 | $19.77 | 87.8 |
| 4 | o4 Reasoning | OpenAI | 1000000 | $19.69 | 87.5 |
| 5 | Grok 4 Max | xAI | 2000000 | $19.70 | 86.6 |
| 6 | Grok 4 Reasoning | xAI | 2000000 | $19.67 | 87.8 |
| 7 | Claude Opus 4.5 Max | Anthropic | 1000000 | $20.90 | 87.8 |
| 8 | Claude Opus 4.5 | Anthropic | 400000 | $19.42 | 87.7 |
| 9 | Gemini 3 Pro Reasoning | Google DeepMind | 200000 | $19.69 | 87.5 |
| 10 | Claude Opus 4.5 Turbo | Anthropic | 2000000 | $19.57 | 85.7 |
What this score means
On MATH-500, Codestral Instruct sits at #256 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 18.6 points. The median model in this index scores 76.0, which puts Codestral Instruct above the midpoint.
Mistral AI models average 69.1 on this benchmark. Codestral Instruct is 9.0 points above that provider line, so it is a stronger result than the average Mistral AI model.
Among multimodal models, the average is 81.3. Codestral Instruct is 3.2 points below that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.
Read a 78.1 as a relative signal, not an absolute guarantee. Benchmark scores depend on prompt format, evaluation harness and contamination controls. Use this page to narrow the shortlist, then test the model on your own data.
Price context
At $4.01 per million input tokens, Codestral Instruct is above the median input price of $4.00 across the 600 models scored on MATH-500. The models immediately around it in the ranking are shown below so you can compare score and price together.
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| Llama 3.3 Groq Chat | Groq | 32768 | $4.06 | 76.8 |
| MiniMax-Text Chat | MiniMax | 128000 | $4.26 | 77.8 |
| Yi-Large Instruct | 01.AI | 32768 | $3.48 | 73.4 |
| Yi-Lightning Instruct | 01.AI | 128000 | $4.16 | 76.5 |
| Codestral Instruct | Mistral AI | 65536 | $4.01 | 75.1 |
| Hunyuan-Turbo | Tencent | 128000 | $10.55 | 75.8 |
| Llama 3 Baseten | Baseten | 128000 | $3.62 | 74.9 |
Other benchmarks for Codestral Instruct
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 78.4 | 228 | 62th | |
| GPQA Diamond | 69.2 | 287 | 52th | |
| SWE-bench Verified | 64.3 | 225 | 63th | |
| HumanEval | 82.5 | 171 | 72th | |
| AIME 2025 | 68.0 | 295 | 51th | |
| LiveCodeBench | 66.1 | 272 | 55th | |
| IFEval | 84.2 | 209 | 65th | |
| TruthfulQA | 78.2 | 248 | 59th | |
| HellaSwag | 87.3 | 161 | 73th | |
| MMMU | 70.0 | 302 | 50th | |
| Arena Elo | 1394.4 | 231 | 62th |
FAQ
What score does Codestral Instruct get on MATH-500?
Codestral Instruct scores 78.1 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.
How does Codestral Instruct rank on MATH-500?
It ranks #256 of 600 models, in the 57th percentile. The leader is GPT-5.2 Max at 96.7.
Is Codestral Instruct good at MATH-500?
Yes, relative to the index: it is above the median and inside the top half of scores. The result should be read alongside its price and context window.
How is the MATH-500 score calculated?
MATH-500 is a mathematics benchmark. Scores in this index are modelled estimates on a 0–100 scale (or Elo for Arena), derived from capability tier and benchmark difficulty. They are not official leaderboard results.
What does Codestral Instruct cost?
Codestral Instruct costs $4.01 per million input tokens and $16.29 per million output tokens.