Mistral-Small-24B-Base-2501: benchmark scores, price and ranking
Mistral-Small-24B-Base-2501 from mistralai ranks #408 of 743 LLMs on the LLMs Tiger aggregate benchmark score (47.7), based on 1 benchmark results captured up to 2026-10-13.
- Organisation
- mistralai
- Type
- Open-weight / local model
- Open weights
- Yes
- Aggregate rank
- #408 of 743 (score 47.7)
Across the 1 benchmark where at least ten models are scored, Mistral-Small-24B-Base-2501 is in the top 10% on 0 and in the top half on 0.
Mistral-Small-24B-Base-2501 benchmark results
| Benchmark | Score | Rank | Source | Captured |
|---|---|---|---|---|
| MMLU-Pro | 54.4% | #70 of 136 | HuggingFace MMLU-Pro leaderboard | 2026-10-13 |
About Mistral-Small-24B-Base-2501
Mistral-Small-24B-Base-2501 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-24B-Base-2501 stands
On our aggregate score, Mistral-Small-24B-Base-2501 is #408 of 743 ranked models, around the middle of the table. Its score is 47.7; the scale is centred on 50, so it sits 2.3 points below the typical model. That beats 45% of the ranked field. Among the 10 ranked mistralai models it is #4. The next one up is Mistral-Large-Instruct-2407 at 49.3. The next one down is Mistral-Small-Instruct-2409 at 46.9.
Mistral-Small-24B-Base-2501, benchmark by benchmark
Mistral-Small-24B-Base-2501 lands below the middle on MMLU-Pro: 54.4%, #70 of 136, with 51% of the field scoring higher. Darwin-180B-RSI leads at 88.1%; the closest result above is DeepSeek-V2-Chat at 54.8%. It covers 57-subject knowledge + reasoning. The board median is 55.3%, so Mistral-Small-24B-Base-2501 is 0.9 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
- #405 Muse Code + Muse Spark 1.3 (47.8)
- #406 DeepSeek-V3.2 (47.7)
- #407 Grok 4 (Fast Reasoning) (47.7)
- #409 Gemini 2.5 Pro (Thinking 32K) (47.7)
- #410 GLM-4.7 (47.7)
- #411 Mistral Large 4 (high) (47.7)
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-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