Mistral Large 3 Instruct on HumanEval: score, rank and what it means
Mistral Large 3 Instruct scores 84.2 on HumanEval, placing it #129 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.
Score distribution
The chart shows the top 10 models on HumanEval, with Mistral Large 3 Instruct highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|---|
| 1 | GPT-5.2 Pro | OpenAI | 2000000 | $21.32 | 89.6 |
| 2 | Gemini 3 Pro Pro | Google DeepMind | 200000 | $19.80 | 87.3 |
| 3 | o4 Max | OpenAI | 2000000 | $19.51 | 86.2 |
| 4 | Grok 4 Reasoning | xAI | 2000000 | $19.67 | 87.8 |
| 5 | Claude Opus 4.5 | Anthropic | 400000 | $19.42 | 87.7 |
| 6 | GPT-5.2 Max | OpenAI | 1000000 | $21.39 | 89.2 |
| 7 | Claude Opus 4.5 Pro | Anthropic | 200000 | $20.98 | 89.1 |
| 8 | Grok 4 Max | xAI | 2000000 | $19.70 | 86.6 |
| 9 | GPT-5.2 Turbo | OpenAI | 1000000 | $20.73 | 87.4 |
| 10 | GPT-5.1 Reasoning | OpenAI | 400000 | $20.27 | 88.3 |
What this score means
On HumanEval, Mistral Large 3 Instruct sits at #129 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 12.6 points. The median model in this index scores 77.4, which puts Mistral Large 3 Instruct above the midpoint.
Mistral AI models average 71.6 on this benchmark. Mistral Large 3 Instruct is 12.6 points above that provider line, so it is a stronger result than the average Mistral AI model.
Among multimodal models, the average is 82.2. Mistral Large 3 Instruct is 2.0 points above that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.
Read a 84.2 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 $5.31 per million input tokens, Mistral Large 3 Instruct is above the median input price of $4.00 across the 600 models scored on HumanEval. 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 |
|---|---|---|---|---|
| Doubao 1.5 Pro Pro | ByteDance | 128000 | $14.10 | 80.2 |
| QwQ | Alibaba Cloud | 128000 | $4.57 | 78.6 |
| Kimi K1.5 Chat | Moonshot AI | 128000 | $5.11 | 80.2 |
| MiniMax-M2 Chat | MiniMax | 200000 | $5.02 | 80.2 |
| Mistral Large 3 Instruct | Mistral AI | 400000 | $5.31 | 81.1 |
| Nova Pro Pro | Amazon | 200000 | $13.03 | 79.5 |
| Doubao 1.5 Pro Max | ByteDance | 400000 | $14.93 | 81.2 |
Other benchmarks for Mistral Large 3 Instruct
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 82.3 | 116 | 81th | |
| GPQA Diamond | 79.8 | 60 | 90th | |
| SWE-bench Verified | 71.9 | 76 | 87th | |
| MATH-500 | 83.4 | 140 | 77th | |
| AIME 2025 | 76.2 | 137 | 77th | |
| LiveCodeBench | 75.1 | 94 | 84th | |
| IFEval | 87.6 | 113 | 81th | |
| TruthfulQA | 85.5 | 60 | 90th | |
| HellaSwag | 89.1 | 110 | 82th | |
| MMMU | 76.5 | 125 | 79th | |
| Arena Elo | 1446.2 | 88 | 85th |
FAQ
What score does Mistral Large 3 Instruct get on HumanEval?
Mistral Large 3 Instruct scores 84.2 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.
How does Mistral Large 3 Instruct rank on HumanEval?
It ranks #129 of 600 models, in the 79th percentile. The leader is GPT-5.2 Pro at 96.8.
Is Mistral Large 3 Instruct good at HumanEval?
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 HumanEval score calculated?
HumanEval is a coding 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 Mistral Large 3 Instruct cost?
Mistral Large 3 Instruct costs $5.31 per million input tokens and $22.47 per million output tokens.