Magistral Small 1.1 Building upon Mistral Small 3.1 (2503), 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. Learn more about Magistral in our blog post. The model was presented in the paper Magistral. Updates compared with Magistral Small 1.0 Magistral Small 1.1 should give you about the same performance as Magistral Small 1.0 as seen in the benchmark results. The update involves the following features: Better tone and model behaviour. You should experiment better LaTeX and Markdown formatting, and shorter answers on easy general prompts. The model is less likely to enter infinite generation loops. [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. The reasoning prompt is now given in the system prompt. Key Features Reasoning: Capable of long chains of reasoning traces before providing an answer…
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