Mistral-Large-Instruct-2411: benchmark scores, price and ranking
Mistral-Large-Instruct-2411 from mistralai ranks #254 of 743 LLMs on the LLMs Tiger aggregate benchmark score (49.6), based on 1 benchmark results captured up to 2026-10-13.
- Organisation
- mistralai
- Type
- Open-weight / local model
- Open weights
- Yes
- Aggregate rank
- #254 of 743 (score 49.6)
Across the 1 benchmark where at least ten models are scored, Mistral-Large-Instruct-2411 is in the top 10% on 0 and in the top half on 1.
Mistral-Large-Instruct-2411 benchmark results
| Benchmark | Score | Rank | Source | Captured |
|---|---|---|---|---|
| MMLU-Pro | 67.9% | #46 of 136 | HuggingFace MMLU-Pro leaderboard | 2026-10-13 |
About Mistral-Large-Instruct-2411
Mistral-Large-Instruct-2411 is an open-weight model that can run on your own hardware from mistralai. No API price is listed for it yet. We hold 1 benchmark result for it across 1 area, and none is in the top tenth of its board.
Where Mistral-Large-Instruct-2411 stands
On our aggregate score, Mistral-Large-Instruct-2411 is #254 of 743 ranked models, around the middle of the table. Its score is 49.6; the scale is centred on 50, so it sits 0.4 points below the typical model. That beats 66% of the ranked field. Among the 10 ranked mistralai models it is #2. The next one up is Mistral-Small-4-119B-2603 at 49.9. The next one down is Mistral-Large-Instruct-2407 at 49.3.
Mistral-Large-Instruct-2411, benchmark by benchmark
MMLU-Pro puts Mistral-Large-Instruct-2411 at 67.9%, #46 of 136. That beats 66% of the models tested, but 20.2 points short of Darwin-180B-RSI (88.1%). The results either side are qwen3-235b-a22b (68.2%) and Hunyuan-A13B-Instruct (67.3%). It covers 57-subject knowledge + reasoning. The board median is 55.3%, so Mistral-Large-Instruct-2411 is 12.7 points above it. Source: HuggingFace MMLU-Pro leaderboard, captured 2026-10-13.
Reading these numbers
The 1 score on this page comes from 1 source: HuggingFace MMLU-Pro leaderboard (1). No official leaderboard supplied any of them, so treat them as third-party measurements. With 1 results the aggregate rank can move a lot when one new score arrives.
Models ranked nearby
- #251 ollama/qwen2.5:32b-instruct-q8_0 (49.6)
- #252 qwen3.5-4b (none) (49.6)
- #253 Qwen3.5 Plus (49.6)
- #255 DeepSeek v4 Flash (max) (49.6)
- #256 gpt-4o-2024-11-20 (49.6)
- #257 claude-haiku-4-5-20251001_16K (49.5)
More from mistralai
- Mistral-Small-4-119B-2603 (#226, 49.9)
- Mistral-Large-Instruct-2407 (#280, 49.3)
- Mistral-Small-24B-Base-2501 (#408, 47.7)
- Mistral-Small-Instruct-2409 (#474, 46.9)
- Mathstral-7B-v0.1 (#540, 46.1)
- Mixtral-8x7B-v0.1 (#550, 45.9)
Compare it on the live leaderboard → · How the aggregate score works