Mistral AI Releases Magistral Reasoning Models: 24B Open-Source and Enterprise Versions Score 70.7% and 73.6% on AIME2024

Mistral AI has released Magistral, its first reasoning model line, in two versions: Magistral Small (24B parameters, Apache 2.0) and Magistral Medium (enterprise). According to Mistral AI, Magistral Medium scored 73.6% on AIME2024 (90% with majority voting at 64 samples), while the open-source Small version achieved 70.7% (83.3% with voting).

Technical Specifications

Magistral Small:

• 24 billion parameters
• Apache 2.0 license (open-source)
• Available on Hugging Face for self-deployment
• AIME2024: 70.7% (single attempt), 83.3% (majority voting @64)

Magistral Medium:

• Parameter count not disclosed
• Enterprise-only version
• AIME2024: 73.6% (single attempt), 90% (majority voting @64)
• Available via La Plateforme API, Le Chat, Amazon SageMaker
• Coming soon to IBM WatsonX, Azure AI, Google Cloud Marketplace

Core Capabilities

Both models feature chain-of-thought reasoning that operates natively across multiple languages and alphabets, including English, French, Spanish, German, Italian, Arabic, Russian, and Simplified Chinese. Mistral AI emphasizes the models are designed for multi-step logic with transparent, traceable thought processes.

The company claims Magistral Medium achieves up to 10x faster token throughput than most competitors when using "Flash Answers" mode in Le Chat, though specific token-per-second figures were not provided.

Target Applications

Mistral AI positions Magistral for:

• Legal research and compliance (with auditable reasoning chains)
• Financial forecasting and risk modeling
• Software development and system architecture
• Strategic planning and operational optimization
• Creative writing and content generation

The models are designed for use cases requiring "longer thought processing and better accuracy than with non-reasoning LLMs," according to the company.

Pricing and Access

Pricing for Magistral Medium API access was not disclosed. Magistral Small is free to download and deploy under Apache 2.0 license. Enterprise customers can request on-premises deployments through Mistral's sales team.

Research Publication

Mistral AI released an accompanying research paper covering training infrastructure, reinforcement learning algorithms, and evaluations. The company stated it aims to "iterate the model quickly" with constant improvements expected.

What This Means

Mistral's entry into reasoning models with an open-source 24B parameter option creates a new benchmark for accessible chain-of-thought models. The AIME2024 scores place both versions competitively within the current reasoning model landscape, though direct comparisons require knowing context windows and pricing structures still undisclosed for the Medium version. The multilingual chain-of-thought capability addresses a genuine gap in existing reasoning models, which typically perform best in English. However, the 10x speed claim lacks the specific comparative data needed for verification.