Magistral is the first reasoning model released by Mistral, designed to meet the demands of complex tasks.
Model Versions
Magistral Small:
- Parameter Count: 24 billion (24B).
- Open-source version under the Apache 2.0 license, allowing users to freely use, modify, and distribute.
- Suitable for environments with a single RTX 4090 GPU or 32GB of RAM.
- This version is available for download on the Hugging Face platform and is designed to support multilingual reasoning tasks.
Magistral Medium:
- A more powerful enterprise-grade version designed for high-complexity tasks.
- Currently in preview, accessible via Mistral’s Le Chat interface or API.
- This version outperforms Magistral Small in terms of performance and is suitable for enterprise needs.
Model Features
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Reasoning Capability: Magistral can perform long-chain reasoning, analyzing problems step-by-step to provide answers. This makes it highly effective in handling complex tasks, especially those requiring multi-step logic.
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Multilingual Support: The model supports multiple languages including English, French, German, Spanish, Arabic, and Simplified Chinese, enabling effective reasoning in diverse linguistic environments.
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Transparency and Verifiability: Magistral is designed with a traceable reasoning process, allowing users to view the model’s logical steps. This feature is especially important in high-stakes fields like law, finance, and healthcare, providing necessary compliance and auditability.
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Open Source and Licensing: The Magistral Small version is released under the Apache 2.0 open-source license, granting developers and researchers the flexibility to innovate and build upon it.
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Context Window: The model has a context window of 128,000 tokens, though performance may degrade beyond 40,000 tokens. Therefore, it is recommended to set the maximum model length at 40,000 tokens.
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High Performance: In Mistral’s “Le Chat” interface, the enterprise version of the model responds up to 10 times faster than many competitors, making it ideal for applications requiring rapid responses.
Application Scenarios
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Finance and Risk Assessment: In the financial sector, Magistral can be used for complex risk evaluations and financial forecasting, aiding professionals in making data-driven decisions. Its transparent reasoning process ensures traceability for compliance.
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Legal and Compliance: Legal professionals can leverage Magistral for legal analysis and compliance reviews. The model’s traceability and logical transparency provide the auditability required in high-risk environments.
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Software Development and Data Engineering: In software development, Magistral enhances efficiency in project planning, backend architecture design, and complex coding tasks. Its multi-step logic capabilities enable developers to better manage and optimize code.
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Science and Engineering: Magistral performs well in scientific research, capable of solving complex mathematical and physical problems, and supporting applications such as physical simulations. This makes it highly valuable for educational and research institutions.
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Creative Writing and Content Generation: The model is also recommended as a creative writing companion, capable of generating coherent and imaginative narratives, making it suitable for storytelling and content creation.
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Multilingual Support: Magistral supports reasoning in multiple languages, including English, French, German, and Chinese, making it suitable for global applications and diverse user backgrounds.
