Mistral: Magistral Small 2506

Text input Text output
Author's Description

Magistral Small is a 24B parameter instruction-tuned model based on Mistral-Small-3.1 (2503), enhanced through supervised fine-tuning on traces from Magistral Medium and further refined via reinforcement learning. It is optimized for reasoning and supports a wide multilingual range, including over 20 languages.

Key Specifications
Cost
$$$$
Context
40K
Parameters
24B (Rumoured)
Released
Jun 10, 2025
Speed
Ability
Reliability
Supported Parameters

This model supports the following parameters:

Stop Presence Penalty Temperature Seed Structured Outputs Response Format Frequency Penalty Max Tokens Include Reasoning Tool Choice Top P Tools Reasoning
Features

This model supports the following features:

Tools Reasoning Structured Outputs Response Format
Performance Summary

Mistral: Magistral Small 2506, a 24B parameter instruction-tuned model, demonstrates competitive response times, performing among the faster models with a speed ranking in the 48th percentile. It also offers competitive pricing, ranking in the 42nd percentile. A notable strength is its exceptional reliability, ranking in the 92nd percentile, indicating consistent and usable responses with minimal technical issues. In terms of specific benchmarks, the model shows strong performance in Coding (85.0% accuracy, 68th percentile) and Email Classification (96.0% accuracy), though the latter comes with a higher cost and slower duration. Its Instruction Following capabilities are a standout, achieving a top 3 ranking in speed, despite a moderate 46.0% accuracy. However, the model exhibits weaknesses in Ethics (88.0% accuracy, 24th percentile), Reasoning (50.0% accuracy, 36th percentile), and General Knowledge (71.0% accuracy, 23rd percentile), where its accuracy and percentile rankings are lower. While generally competitive in speed and price, its performance varies significantly across different cognitive tasks, excelling in structured tasks like coding and classification but showing room for improvement in more abstract reasoning and broad knowledge domains.

Model Pricing

Current Pricing

Feature Price (per 1M tokens)
Prompt $0.5
Completion $1.5

Price History

Available Endpoints
Provider Endpoint Name Context Length Pricing (Input) Pricing (Output)
Mistral
Mistral | mistralai/magistral-small-2506 40K $0.5 / 1M tokens $1.5 / 1M tokens
Kluster
Kluster | mistralai/magistral-small-2506 40K $0.5 / 1M tokens $1.5 / 1M tokens
Enfer
Enfer | mistralai/magistral-small-2506 32K $0.5 / 1M tokens $1.5 / 1M tokens
Benchmark Results
Benchmark Category Reasoning Free Executions Accuracy Cost Duration
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