Magistral Small 1.2 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. Learn more about Magistral in our blog post. 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 prom…
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