Magistral Small
Magistral Small is Mistral's entry-level reasoning model, bringing structured chain-of-thought thinking to a compact and cost-effective package. It's designed for applications that benefit from deliberate, step-by-step reasoning without the compute overhead of larger thinking models.
Magistral Small produces visible reasoning traces that show its work, making it particularly useful for educational applications, explainable AI systems, and any use case where users need to verify the model's logic. It handles arithmetic, basic logic puzzles, and structured problem-solving reliably.
Key Features
Structured chain-of-thought reasoning with visible thinking traces
Cost-effective reasoning — deliberate thinking at small-model prices
128K token context for processing longer analytical problems
Good performance on arithmetic, logic, and structured problem-solving
Fast time-to-first-token compared to larger reasoning models
Ideal Use Cases
Educational tutoring with step-by-step explanations
Lightweight analytical queries — quick math, logic checks, fact verification
Explainable AI applications where reasoning transparency is required
Automated grading and assessment with visible scoring rationale
Example Prompts for Magistral Small
Technical Specifications
| Context Window | 128K tokens |
| Modality | Text → Text |
| Provider | Mistral |
| Category | Reasoning |
| Thinking Mode | Structured chain-of-thought |
| Latency | Low — optimized for interactive use |
| Best For | Cost-effective reasoning tasks |
Frequently Asked Questions
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