Magistral
Mistral AIMistral's reasoning model line, launched June 2025 in two tiers: the open-weight Magistral Small, a 24B model distilled from Magistral Medium traces with RL on top, and the API-only Magistral Medium. The current Small 1.2 adds a vision encoder and reasons in a dedicated thinking block, and fits on a single consumer GPU once quantized.
Mistral's reasoning line beside devstral (coding) and codestral (completion) on the map. Openness is read on the distributed SKU, Magistral Small, since Medium is API-only; the RL pipeline is described in the Magistral paper but not released.
Openness
3 high confidence- weights
- open(Magistral Small 2506/2507/2509, ungated Apache-2.0 on HF)
- post-training-data
- described(SFT from Magistral Medium traces + RLVR, described in the paper, not released)
- code
- closed(no post-training pipeline released
- license
- Apache-2.0(OSI)
Every distributed Magistral Small release ships Apache-2.0 weights, ungated on the Hub, but the post-training mixture is only described in the paper, not released, and no pipeline ships. Magistral Medium, API-only, falls outside the distributed SKUs this reading covers, leaving the family open weights with a closed recipe.
- https://huggingface.co/api/models/mistralai/Magistral-Small-2509 recorded 2026-10-07
Model API for mistralai/Magistral-Small-2509: `gated: false`, `private: false`, cardData.license `apache-2.0`, base_model mistralai/Mistral-Small-3.2-24B-Instruct-2506, safetensors weights listed.
- https://huggingface.co/mistralai/Magistral-Small-2509/raw/main/README.md recorded 2026-10-07
Card: built on Mistral Small 3.2 (2506) "with added reasoning capabilities", "undergoing SFT from Magistral Medium traces and RL on top"; "Open license allowing usage and modification for both commercial and non-commercial purposes" under the Apache 2.0 heading; and a "Benchmark Results" table for Magistral Medium 1.2 and Small 1.2. No training mixture or pipeline is released.
- https://mistral.ai/news/magistral recorded 2026-10-07
The Magistral launch post announces a dual release: "Magistral Small — a 24B parameter open-source version and Magistral Medium — a more powerful, enterprise version", which scopes the license reading to the Small SKUs.
Adoption
2 high confidenceAdoption is measured as Hugging Face downloads summed across the three declared Magistral Small releases. Most of that volume still goes to the original 2506 release rather than the newer 2507 or 2509 updates.
- https://huggingface.co/api/models/mistralai/Magistral-Small-2506 recorded 2026-09-01
80,730 downloads in the trailing 30 days for mistralai/Magistral-Small-2506
- https://huggingface.co/api/models/mistralai/Magistral-Small-2507 recorded 2026-09-01
491 downloads in the trailing 30 days for mistralai/Magistral-Small-2507
- https://huggingface.co/api/models/mistralai/Magistral-Small-2509 recorded 2026-09-01
12,960 downloads in the trailing 30 days for mistralai/Magistral-Small-2509
Capability
4 medium confidenceMagistral Small posts AIME-class math results, 86.14% on AIME 2024, that place it level with DeepSeek-R1, a competitive open-weight reasoner short of the closed frontier. Magistral Medium, the tier's stronger member, scores higher still but is API-only and not counted since it is not distributed as weights.
- https://huggingface.co/mistralai/Magistral-Small-2509/raw/main/README.md recorded 2026-10-07
Benchmark Results table: Magistral Medium 1.2 AIME24 91.82% / AIME25 83.48% / GPQA Diamond 76.26% / LiveCodeBench v5 75.00%; Magistral Small 1.2 AIME24 86.14% / AIME25 77.34%.
Verified 2026-09-27