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Mistral Releases Magistral, Its First-Ever Reasoning AI Models With Transparent Chain-of-Thought

Mistral has released two variants of Magistral — Small, an open-source model, and Medium, aimed at enterprises.

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Highlights
  • Magistral Small is a 24-billion-parameter AI model
  • Both models are capable of multi-step reasoning
  • Magistral Medium can be accessed via Amazon SageMaker
Mistral Releases Magistral, Its First-Ever Reasoning AI Models With Transparent Chain-of-Thought

Mistral is also making Magistral’s reasoning traceable for enterprises in critical sectors

Photo Credit: Mistral

Mistral released its first reasoning-focused artificial intelligence (AI) models on Tuesday. Dubbed Magistral, the large language model (LLM) is available in two variants — Small and Medium. While Magistral Small is an open-source model, the Medium variant is an enterprise-focused closed model. Both models are capable of multi-step reasoning and show transparent chain-of-thought (CoT). The French AI startup highlighted that Magistral is designed for research, strategic planning, and data-driven decision making. A preview version of the reasoning model can also be tried out via the company's Le Chat platform.

Mistral's Magistral Small Is Available With Apache 2.0 Licence

In a newsroom post, the Paris-based AI firm announced the release of the two Magistral models. Magistral Small, the open-weight LLM, is available to download and deploy via Mistral's Hugging Face listing with the Apache 2.0 licence. The model can be used for both academic and commercial use cases.

On the other hand, Magistral Medium is a proprietary model which can be accessed via Amazon SageMaker. It will also be hosted on IBM WatsonX, Azure AI, and Google Cloud Marketplace soon. A preview version of the model can also be experienced in Le Chat or via API on La Plateforme.

Coming to model details, the Magistral Small is a 24 billion parameter model. The parameters of the enterprise version have not been disclosed by the company.

Focusing on Magistral Medium's capabilities, the model is claimed to have scored 73.6 percent on the AIME2024, comparable to DeepSeek-R1. On the other hand, the Small variant is said to have scored 70.7 percent, Mistral said.

Both models can reason natively, and the CoT works in multiple global languages. The company said Magistral can reason in English, French, Spanish, German, Italian, Arabic, Russian, and Simplified Chinese languages.

As with most reasoning models, Magistral can also handle structured calculations, programmatic logic, as well as decision trees and rule-based systems.

Mistral says enterprises and users working in critical fields such as finance, healthcare, government, and law will get traceable reasoning within the models, allowing them to check the logical steps it took to reach a response. This will allow users to audit responses that are more sensitive than others, the company added.

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