
Devstral 2
Mistral's 123B-parameter agentic coding model, built for multi-file software engineering tasks.
Last refreshed: 17 May 2026 · Appears in 1 active topic
Is Devstral 2 the first open-weight coding agent to match closed US frontier models?
Timeline for Devstral 2
Bundled in Le Chat Enterprise enterprise stack
European Tech Sovereignty: Mistral ships Le Chat Enterprise and Medium 3.5What is Mistral Devstral 2 and how does it differ from the original Devstral?
How does Devstral 2 perform on SWE-bench compared to Claude and GPT-4?
Can Devstral 2 be run locally or does it require Mistral's cloud?
Background
Devstral 2 is Mistral AI's second-generation developer agent model, launched in December 2025 alongside the Mistral Vibe CLI. With 123 billion parameters and a 256K-token context window, it is purpose-built for agentic software engineering: autonomously navigating codebases, writing tests, resolving bugs across multiple files, and submitting pull requests. A smaller companion, Devstral Small 2 (24B parameters), targets local and laptop deployment. Mistral announced both models as part of its broader Le Chat Enterprise push .
On the SWE-bench Verified benchmark, a standard for evaluating real-world software engineering in existing repositories, Devstral 2 achieves 72.2% and Devstral Small 2 achieves 68.0% — the highest score of any open-weight model at its parameter count, outperforming several 70B-class competitors. Devstral 2 is released under a modified MIT licence; Devstral Small 2 ships under Apache 2.0. Both are available via Mistral's API and Hugging Face. Mistral claims Devstral 2 is up to 7x more cost-efficient than Claude Sonnet on real-world agentic coding tasks.
Devstral 2 is strategically significant for the European AI stack: it is the only open-weight agent-class coding model with a European company behind it. For regulated industries requiring on-premises agentic AI — banking, defence, healthcare — an EU-origin open-weight model addresses both data-residency and AI-Act compliance concerns that US-origin closed models cannot satisfy.