Mistral Large 3 on SWE-bench Verified: score, rank and what it means
Mistral Large 3 scores 71.3 on SWE-bench Verified, placing it #89 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.
Score distribution
The chart shows the top 10 models on SWE-bench Verified, with Mistral Large 3 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 | Claude Opus 4.5 Pro | Anthropic | 200000 | $20.98 | 89.1 |
| 3 | GPT-5.2 Max | OpenAI | 1000000 | $21.39 | 89.2 |
| 4 | Claude Sonnet 4.5 Max | Anthropic | 1000000 | $19.90 | 87.2 |
| 5 | GPT-5.2 | OpenAI | 2000000 | $19.71 | 88.0 |
| 6 | GPT-5.1 Pro | OpenAI | 200000 | $19.77 | 87.8 |
| 7 | o4 Max | OpenAI | 2000000 | $19.51 | 86.2 |
| 8 | Claude Sonnet 4.5 Reasoning | Anthropic | 400000 | $19.48 | 87.7 |
| 9 | Claude Opus 4.5 Max | Anthropic | 1000000 | $20.90 | 87.8 |
| 10 | Claude Opus 4.5 Reasoning | Anthropic | 2000000 | $20.91 | 88.2 |
What this score means
On SWE-bench Verified, Mistral Large 3 sits at #89 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 10.4 points. The median model in this index scores 61.0, which puts Mistral Large 3 above the midpoint.
Mistral AI models average 54.7 on this benchmark. Mistral Large 3 is 16.6 points above that provider line, so it is a stronger result than the average Mistral AI model.
Among multimodal models, the average is 66.4. Mistral Large 3 is 4.9 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 71.3 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 $5.41 per million input tokens, Mistral Large 3 is above the median input price of $4.00 across the 600 models scored on SWE-bench Verified. 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 |
|---|---|---|---|---|
| Gemini 2.5 Pro Turbo | Google DeepMind | 1000000 | $16.32 | 83.9 |
| Gemini 3 Flash Vision | Google DeepMind | 400000 | $15.06 | 81.9 |
| Grok 3 Pro | xAI | 400000 | $16.61 | 83.8 |
| Grok 3 Turbo | xAI | 128000 | $15.97 | 83.1 |
| Mistral Large 3 | Mistral AI | 128000 | $5.41 | 81.7 |
| Command A Pro | Cohere | 200000 | $14.28 | 81.3 |
| DeepSeek-R1 Base | DeepSeek | 400000 | $5.05 | 80.1 |
Other benchmarks for Mistral Large 3
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 84.6 | 71 | 88th | |
| GPQA Diamond | 79.6 | 65 | 89th | |
| HumanEval | 88.6 | 62 | 90th | |
| MATH-500 | 84.1 | 123 | 80th | |
| AIME 2025 | 78.3 | 110 | 82th | |
| LiveCodeBench | 74.4 | 101 | 83th | |
| IFEval | 89.8 | 75 | 88th | |
| TruthfulQA | 83.7 | 89 | 85th | |
| HellaSwag | 88.2 | 135 | 78th | |
| MMMU | 76.2 | 134 | 78th | |
| Arena Elo | 1448.6 | 76 | 87th |
FAQ
What score does Mistral Large 3 get on SWE-bench Verified?
Mistral Large 3 scores 71.3 on SWE-bench Verified in this index. The benchmark average is 57.5 and the top score is 81.7.
How does Mistral Large 3 rank on SWE-bench Verified?
It ranks #89 of 600 models, in the 85th percentile. The leader is GPT-5.2 Pro at 81.7.
Is Mistral Large 3 good at SWE-bench Verified?
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 SWE-bench Verified score calculated?
SWE-bench Verified 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 cost?
Mistral Large 3 costs $5.41 per million input tokens and $23.83 per million output tokens.