Magistral Small 1.0: benchmark scores, price and ranking
Magistral Small 1.0 from Mistral AI is a recent or sparsely tested model with 1 benchmark result on record; it has not been measured on enough benchmarks shared with other models to receive an aggregate rank. This page lists every score we have, based on 1 benchmark results captured up to 2026-10-13.
- Organisation
- Mistral AI
- Type
- Open-weight / local model
- Open weights
- Yes
- Released
- 2025-06-10 (source: epoch)
- Aggregate rank
- Not ranked yet (too few shared benchmarks)
Across the 1 benchmark where at least ten models are scored, Magistral Small 1.0 is in the top 10% on 0 and in the top half on 1.
Magistral Small 1.0 benchmark results
| Benchmark | Score | Rank | Source | Captured |
|---|---|---|---|---|
| Epoch ECI | 133 | #79 of 204 | Epoch AI Benchmarking Hub | 2026-10-13 |
About Magistral Small 1.0
Magistral Small 1.0 is an open-weight model that can run on your own hardware from Mistral AI. It was released on 2025-06-10, 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 Magistral Small 1.0 stands
Magistral Small 1.0 has 1 result so far and shares too few benchmarks with other models to get an aggregate rank. The rank will appear on its own once more scores are published.
Magistral Small 1.0, benchmark by benchmark
Epoch ECI puts Magistral Small 1.0 at 133, #79 of 204. That beats 61% of the models tested, but 23 points short of Qwen 3.8 Max (156). The results either side are Claude 3.5 Sonnet (October 2024) (134) and Qwen2.5-Max (133). It covers Epoch Capabilities Index: Epoch's own aggregate of ~40 benchmarks. The board median is 127, so Magistral Small 1.0 is 6 points above it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.
Release history
The Mistral AI model released before it was mistral-medium-2505 on 2025-05-07, which scores 45.4. The next one was magistral-small-2506 on 2025-06-10, at 47.0.
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.
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