Magistral Small (24B): Mistral's Open-Source Reasoning Powerhouse with SFT+RL
Introduction Magistral Small (24B) is Mistral AI’s open-source reasoning-focused language model with 24 billion parameters. Built on the foundation of the Mistral Small 3.1 model, it utilizes a specialized training regimen combining Supervised Fine-Tuning (SFT) traces from its larger sibling, Magistral Medium, with a custom Reinforcement Learning (RL) pipeline. This hybrid SFT+RL approach enhances its performance in tasks requiring long chains of logic, particularly in mathematics and coding. TL;DR: Magistral Small (24B) is a highly efficient, 24-billion-parameter open-source model from Mistral AI, released under the Apache 2.0 License. Its standout feature is superior reasoning performance in math and code, achieved through a unique SFT combined with RL training pipeline. The model’s compact size allows for easy local deployment, potentially running on a single RTX 4090 or a 32GB RAM MacBook once quantized. Introduction Magistral Small (24B), released by Mistral AI in June 2025, marks the company’s first model explicitly focused on complex, domain-specific reasoning capabilities [1.3, 2.1]. Built on the foundation of the Mistral Small 3.1 model, the 24-billion-parameter model utilizes a specialized training regimen combining Supervised Fine-Tuning (SFT) traces from its more powerful sibling, Magistral Medium, with a custom Reinforcement Learning (RL) pipeline [1.4, 1.8]. This hybrid SFT+RL approach elevates its performance in tasks requiring long chains of logic, particularly in mathematics and coding. ...