Mistral
availableShows if the model has enough results for an index.Mistral Large
Mistral Large is a model from Mistral. 12 benchmarks count toward its score, in 5 categories.
IndexOverall score out of 100.28.7 ±7.2
CoverageShare of the index weight with results.75%
SpeedOutput tokens per second.67/s
Input / 1MUS dollars per 1M input tokens.$2
Output / 1MUS dollars per 1M output tokens.$6
ContextMaximum tokens in one request.128K
EloLMArena rating and rank.1176 (#316)
The index is a score out of 100. The ± range shows how much it can change.
62,436 votes. Elo shows what people prefer. It does not change the score.
CapabilitiesScore per category, out of 100.
Out of 100Results
12 counted| BenchmarkThe test name. | CategoryThe capability that the test measures. | ResultThe score from the publisher. | IndexThis result as a score out of 100. | RunThe settings of the run. | DateDate of the result. | Published byThe source of the result. |
|---|---|---|---|---|---|---|
| MGSM | Multilingual | 87.2% | — | — | 9 Jan 2026 | Vals AI |
| MGSM | Multilingual | 86.3% | — | — | 9 Jan 2026 | Vals AI |
| MGSM | Multilingual | 85.4% | — | — | 9 Jan 2026 | Vals AI |
| MMLU Pro | Knowledge | 79.8% | 46.3 | — | 1 Sept 2026 | Vals AI |
| MMLU Pro | Knowledge | 74.8% | 38.3 | — | 1 Sept 2026 | Vals AI |
| MATH 500 | Math | 74.4% | 25.0 | — | 9 Jan 2026 | Vals AI |
| MATH 500 | Math | 74.4% | 25.0 | — | 9 Jan 2026 | Vals AI |
| MMLU Pro | Knowledge | 69.7% | 30.3 | — | 1 Sept 2026 | Vals AI |
| GPQA Diamond | Knowledge | 68.4% | 41.4 | — | 1 Sept 2026 | Vals AI |
| MMMU Pro | Multimodal | 66.2% | 35.1 | — | 1 Sept 2026 | Vals AI |
| MMMU Pro | Multimodal | 66.2% | 35.1 | — | 1 Sept 2026 | Vals AI |
| GPQA Diamond | Knowledge | 58.1% | 31.9 | — | 1 Sept 2026 | Vals AI |
| LiveCodeBench | Coding | 55.3% | 34.6 | — | 1 Sept 2026 | Vals AI |
| GPQA Diamond | Knowledge | 47.7% | 22.3 | — | 1 Sept 2026 | Vals AI |
| LiveCodeBench | Coding | 46.2% | 26.4 | — | 1 Sept 2026 | Vals AI |
| AIME | Math | 42.9% | 33.7 | — | 16 Apr 2026 | Vals AI |
| SWE-bench | Coding | 41.4% | 30.7 | — | 1 Sept 2026 | Vals AI |
| SWE-bench | Coding | 41.4% | 30.7 | — | 1 Sept 2026 | Vals AI |
| GPQA diamond | Knowledge | 38.8% | 14.0 | — | — | Epoch AI |
| LiveCodeBench | Coding | 37.1% | 18.1 | — | 1 Sept 2026 | Vals AI |
| AIME | Math | 26.0% | 25.9 | — | 16 Apr 2026 | Vals AI |
| MATH level 5 | Math | 24.5% | 10.7 | — | — | Epoch AI |
| Terminal-Bench 1.0 | Agentic | 21.3% | 29.6 | — | 12 Jan 2026 | Vals AI |
| Terminal-Bench 1.0 | Agentic | 21.3% | 29.6 | — | 12 Jan 2026 | Vals AI |
| AIME | Math | 9.2% | 18.0 | — | 16 Apr 2026 | Vals AI |
| Terminal-Bench 2.0 | Agentic | 9.0% | 29.1 | — | 4 Jun 2026 | Vals AI |
| Terminal-Bench 2.0 | Agentic | 9.0% | 29.1 | — | 4 Jun 2026 | Vals AI |
| IOI v1 | Coding | 4.0% | 42.2 | — | 9 Aug 2026 | Vals AI |
| IOI v1 | Coding | 4.0% | 42.2 | — | 9 Aug 2026 | Vals AI |
| OTIS Mock AIME 2024-2025 | Math | 1.9% | 12.7 | — | — | Epoch AI |
12 benchmarks count, from 27 of 30 results. A grey row does not count. Too few models took that benchmark.