Magistral Small 1.2: Enhanced Multimodal Reasoning

mistralai's Magistral-Small-2509 is a 24 billion parameter multimodal language model, an evolution of Mistral Small 3.2 (2506). It significantly improves upon its predecessor, Magistral Small 1.1, particularly in reasoning and multimodal understanding.

Key Capabilities

• Advanced Reasoning: Capable of generating long chains of reasoning traces, encapsulated by [THINK] and [/THINK] tokens, before providing a final answer. This process is guided by a specific system prompt for optimal results.
• Multimodality: Integrates a vision encoder, allowing it to process and reason based on visual inputs in addition to text. This extends its problem-solving abilities to image-based queries.
• Multilingual Support: Supports dozens of languages, including English, French, German, Japanese, Chinese, and many others.
• Extended Context Window: Features a 128k context window, designed to handle extensive inputs, though performance might see some degradation past 40k tokens.
• Improved Performance: Demonstrates significant performance upgrades over Magistral Small 1.1 across various benchmarks, including AIME24, AIME25, GPQA Diamond, and Livecodebench.
• Refined Output: Offers better LaTeX and Markdown formatting, shorter answers for simple prompts, and reduced likelihood of infinite generation loops.

Good for

• Complex Problem Solving: Ideal for tasks requiring detailed, step-by-step reasoning, especially with its [THINK] token mechanism.
• Multimodal Applications: Suitable for use cases that involve analyzing and responding to both text and image inputs.
• Local Deployment: Designed to be efficient enough for local deployment on hardware like an RTX 4090 or a 32GB RAM MacBook (when quantized).
• Multilingual Interactions: Effective for applications requiring understanding and generation in a wide array of languages.
• Apache 2.0 Licensed: Offers flexibility for both commercial and non-commercial use and modification.