Mistral-Small-Instruct-2409: benchmark scores, price and ranking
Mistral-Small-Instruct-2409 from mistralai ranks #474 of 743 LLMs on the LLMs Tiger aggregate benchmark score (46.9), based on 1 benchmark results captured up to 2026-10-13.
- Organisation
- mistralai
- Type
- Open-weight / local model
- Open weights
- Yes
- Aggregate rank
- #474 of 743 (score 46.9)
Across the 1 benchmark where at least ten models are scored, Mistral-Small-Instruct-2409 is in the top 10% on 0 and in the top half on 0.
Mistral-Small-Instruct-2409 benchmark results
| Benchmark | Score | Rank | Source | Captured |
|---|---|---|---|---|
| MMLU-Pro | 48.4% | #80 of 136 | HuggingFace MMLU-Pro leaderboard | 2026-10-13 |
About Mistral-Small-Instruct-2409
Mistral-Small-Instruct-2409 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-Small-Instruct-2409 stands
On our aggregate score, Mistral-Small-Instruct-2409 is #474 of 743 ranked models, in the lower half. Its score is 46.9; the scale is centred on 50, so it sits 3.1 points below the typical model. That beats 36% of the ranked field. Among the 10 ranked mistralai models it is #5. The next one up is Mistral-Small-24B-Base-2501 at 47.7. The next one down is Mathstral-7B-v0.1 at 46.1.
Mistral-Small-Instruct-2409, benchmark by benchmark
Mistral-Small-Instruct-2409 lands below the middle on MMLU-Pro: 48.4%, #80 of 136, with 58% of the field scoring higher. Darwin-180B-RSI leads at 88.1%; the closest result above is AI21-Jamba-Large-1.5 at 49.5%. It covers 57-subject knowledge + reasoning. The board median is 55.3%, so Mistral-Small-Instruct-2409 is 6.9 points below 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
- #471 Reflection-70B (47.0)
- #472 magistral-small-2506 (47.0)
- #473 nemotron-3-ultra (47.0)
- #475 Qwen3-32B (46.9)
- #476 GPT-4 Turbo Preview (Nov 2023) (46.9)
- #477 GPT-4 Turbo Preview (January 2024) (46.9)
More from mistralai
- Mistral-Small-4-119B-2603 (#226, 49.9)
- Mistral-Large-Instruct-2411 (#254, 49.6)
- Mistral-Large-Instruct-2407 (#280, 49.3)
- Mistral-Small-24B-Base-2501 (#408, 47.7)
- 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