mistral-small-2402: benchmark scores, price and ranking
mistral-small-2402 from Mistral AI ranks #493 of 743 LLMs on the LLMs Tiger aggregate benchmark score (46.7), based on 1 benchmark results captured up to 2026-10-13.
- Organisation
- Mistral AI
- Type
- Open-weight / local model
- Open weights
- Yes
- Released
- 2024-02-26 (source: epoch)
- Aggregate rank
- #493 of 743 (score 46.7)
Across the 1 benchmark where at least ten models are scored, mistral-small-2402 is in the top 10% on 0 and in the top half on 0.
mistral-small-2402 benchmark results
| Benchmark | Score | Rank | Source | Captured |
|---|---|---|---|---|
| DTBench | 53.0% | #120 of 146 | Epoch AI Benchmarking Hub | 2026-10-13 |
About mistral-small-2402
mistral-small-2402 is an open-weight model that can run on your own hardware from Mistral AI. It was released on 2024-02-26, according to Epoch AI. 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-2402 stands
On our aggregate score, mistral-small-2402 is #493 of 743 ranked models, in the lower half. Its score is 46.7; the scale is centred on 50, so it sits 3.3 points below the typical model. That beats 34% of the ranked field. Among the 44 ranked Mistral AI models it is #15. The next one up is mistral-medium-2312 at 46.7. The next one down is Mistral Small 4 at 46.5.
mistral-small-2402, benchmark by benchmark
DTBench is a weak spot. mistral-small-2402 scores 53.0%, #120 of 146, behind 82% of the models measured. The leader, Claude Opus 5.5 (max), reaches 98.9%. It covers dynamic tool-use benchmark. The board median is 68.8%, so mistral-small-2402 is 15.8 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.
Release history
The Mistral AI model released before it was mistral-large-2402 on 2024-02-26, which scores 42.8. The next one was Mixtral-8x22B-Instruct-v0.1 on 2024-04-17, at 43.5.
Reading these numbers
The 1 score on this page comes from 1 source: Epoch AI Benchmarking Hub (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
- #490 grok-4-1-fast-reasoning (46.7)
- #491 Llama 4 Maverick Instruct (46.7)
- #492 internlm2-chat-20b (46.7)
- #494 mimo-v2.5 (46.7)
- #495 Claude Sonnet 3.5 (46.7)
- #496 MCTS Refine 7B (46.7)
More from Mistral AI
- Mistral Large 2 (2407) (#231, 49.9)
- codestral-2405 (#352, 48.4)
- pixtral-large-2411 (#360, 48.3)
- Codestral-22B-v0.1-Q4_K_M (#392, 48.0)
- codestral:22b-v0.1-q8_0 (#393, 48.0)
- Mistral Large 4 (high) (#411, 47.7)
Compare it on the live leaderboard → · How the aggregate score works