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Model details

Magistral Small 2506

Magistral Small 2506 is a 24-billion-parameter language model developed by Mistral AI as part of its first reasoning-focused family. It is built on the Mistral Small 3 base, extending that lineage with added reasoning capabilities and multilingual support across dozens of languages. Within the Magistral lineup, this variant ships as the open-weights, Apache 2 licensed option, while a larger sibling called Magistral Medium is offered as an API-only model. The Hugging Face repository is mistralai/Magistral-Small-2506, and Mistral also publishes an official GGUF quantization for local runtimes.

According to the Magistral-Small-2506 model card, the model advertises a 128k context window but recommends capping practical usage at around 40k tokens, where performance remains reliable before degradation may set in. The model is aimed at reasoning-heavy workloads, fast-response conversational agents, and applications that combine strong language understanding with structured problem solving. Its blend of a relatively compact parameter count, open licensing, and dedicated reasoning training makes it a practical choice for teams that want Mistral's chain-of-thought style generation without committing to a larger proprietary deployment.

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IO.NET
Model key
mistralai/Magistral-Small-2506
Release date
Jun 1, 2025
Last updated
Jun 1, 2025
Knowledge cutoff
2025-01
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$0.50
Output token cost
$1.50

Limits

Output tokens
4,096 tokens
Context window
128,000 tokens

Latest news about Magistral Small 2506

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Coverage

The Unsloth GGUF model card for Magistral-Small-2506 confirms it is a reasoning-focused model explicitly named with the 2506 variant identifier, built upon Mistral Small 3.1 (2503) with added reasoning capabilities. It was trained using SFT from Magistral Medium traces followed by RL, contains 24 billion parameters, an The model card documents benchmark results for Magistral Small 2506: 70.68% on AIME24 pass@1, 62.76% on AIME25 pass@1, 68.18% on GPQA Diamond, and 55.84% on Livecodebench (v5), compared against Magistral Medium's higher scores. It highlights multilingual support across dozens of languages including English, French, Ger

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