Magistral
Magistral
MistralAI's open-weight reasoning model. 24B dense transformer model supporting up to 128K token context window. The model is capable of long chains of reasoning traces before providing answers.
Memory Requirements
To run the smallest Magistral, you need at least 15 GB of RAM. The largest one may require up to 19 GB.
Capabilities
Magistral models support tool use, vision input, and reasoning. They are available in gguf and mlx.
About Magistral
Note: only the newest Magistral (2509) supports vision input.
Building upon Mistral Small 3.2 (2506), with added reasoning capabilities, undergoing SFT from Magistral Medium traces and RL on top, it's a small, efficient reasoning model with 24B parameters.
Magistral Small can be deployed locally, fitting within a single RTX 4090 or a 32GB RAM MacBook once quantized.
The model was presented in the paper Magistral.
Updates compared with Magistral Small 1.1
- Multimodality: The model now has a vision encoder and can take multimodal inputs, extending its reasoning capabilities to vision.
- Performance upgrade: Magistral Small 1.2 should give you significantly better performance than Magistral Small 1.1 as seen in the benchmark results.
- Better tone and persona: You should experience better LaTeX and Markdown formatting, and shorter answers on easy general prompts.
- Finite generation: The model is less likely to enter infinite generation loops.
- Special think tokens: [THINK] and [/THINK] special tokens encapsulate the reasoning content in a thinking chunk. This makes it easier to parse the reasoning trace and prevents confusion when the '[THINK]' token is given as a string in the prompt.
- Reasoning prompt: The reasoning prompt is given in the system prompt.
Key Features
- Reasoning: Capable of long chains of reasoning traces before providing an answer.
- Multilingual: Supports dozens of languages, including English, French, German, Greek, Hindi, Indonesian, Italian, Japanese, Korean, Malay, Nepali, Polish, Portuguese, Romanian, Russian, Serbian, Spanish, Turkish, Ukrainian, Vietnamese, Arabic, Bengali, Chinese, and Farsi.
- Vision: Vision capabilities enable the model to analyze images and reason based on visual content in addition to text.
- Apache 2.0 License: Open license allowing usage and modification for both commercial and non-commercial purposes.
- Context Window: A 128k context window. Performance might degrade past 40k but Magistral should still give good results. Hence we recommend to leave the maximum model length to 128k and only lower if you encounter low performance.
Benchmark Results
| Model | AIME24 pass@1 | AIME25 pass@1 | GPQA Diamond | Livecodebench (v5) |
|---|---|---|---|---|
| Magistral Medium 1.2 | 91.82% | 83.48% | 76.26% | 75.00% |
| Magistral Medium 1.1 | 72.03% | 60.99% | 71.46% | 59.35% |
| Magistral Medium 1.0 | 73.59% | 64.95% | 70.83% | 59.36% |
| Magistral Small 1.2 | 86.14% | 77.34% | 70.07% | 70.88% |
| Magistral Small 1.1 | 70.52% | 62.03% | 65.78% | 59.17% |
| Magistral Small 1.0 | 70.68% | 62.76% | 68.18% | 55.84% |