Mistral AI has introduced Devstral 2, a next generation coding model family for software engineering agents, together with Mistral Vibe CLI, an open source command line coding assistant that runs inside the terminal or IDEs that support the Agent Communication Protocol.
Devstral 2 and Devstral Small 2, model sizes, context and benchmarks
Devstral 2 is a 123B parameter dense transformer with a 256K token context window. It reaches 72.2 percent on SWE-bench Verified, which places it among the strongest open weight models for software engineering tasks. The model is released as open weights under a modified MIT license and is currently free to use via the Mistral API.
Devstral Small 2 is a 24B parameter model with the same 256K context window. It scores 68.0 percent on SWE-bench Verified and sits in the range of models that are up to 5 times larger in parameter count. It is released under the Apache 2.0 license, which is a standard permissive license for production use.
Both models are described as open source and permissively licensed and are positioned as state of the art coding models for agentic workloads. Mistral reports that Devstral 2 is up to 7 times more cost efficient than Claude Sonnet on real world coding tasks at similar quality, which is important for continuous agent workloads.
In terms of model size relative to frontier systems, Devstral 2 and Devstral Small 2 are 5 times and 28 times smaller than DeepSeek V3.2, and 8 times and 41 times smaller than Kimi K2.
Built for production grade coding workflows
Devstral 2 is designed for software engineering agents that need to explore repositories, track dependencies and orchestrate edits across many files while maintaining architecture level context. The model can detect failures, retry with corrections and support tasks such as bug fixing or modernization of legacy systems at repository scale.
Mistral states that Devstral 2 can be fine tuned to favor specific programming languages or to optimize for very large enterprise codebases. Devstral Small 2 brings the same design goals to a smaller footprint that is suitable for local deployment, tight feedback loops and fully private runtimes. It also supports image inputs and can drive multimodal agents that must reason over both code and visual artifacts such as diagrams or screenshots.
Human evaluations against DeepSeek V3.2 and Claude Sonnet 4.5
To test real world coding behavior, Mistral evaluated Devstral 2 against DeepSeek V3.2 and Claude Sonnet 4.5 using tasks scaffolded through the Cline agent tool. In these human evaluations Devstral 2 shows a clear advantage over DeepSeek V3.2 with a 42.8 percent win rate versus a 28.6 percent loss rate.
Mistral Vibe CLI, a terminal native coding agent
Mistral Vibe CLI is an open source command line coding assistant written in Python and powered by Devstral models. It explores, modifies and executes changes across a codebase using natural language in the terminal, or inside IDEs that support the Agent Communication Protocol such as Zed where it is available as an extension.The project is released under the Apache 2.0 license on GitHub.
Vibe CLI provides a chat style interface on top of several key tools:
- Project aware context, it scans the file structure and Git status to build a working view of the repository.
- Smart references, it supports @ autocomplete for files, ! for shell commands and slash commands for configuration changes.
- Multi file orchestration, it reasons over the full codebase, not only the active buffer, to coordinate architecture level changes and reduce pull request cycle time.
- Persistent history, autocompletion and themes tuned for daily use in the terminal.
Developers configure Vibe CLI through a simple config.toml file where they can point to Devstral 2 via the Mistral API or to other local or remote models. The tool supports programmatic runs, auto approval toggles for tool execution and granular permissions so that risky operations in sensitive repositories require confirmation.
Key Takeaways
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Asif Razzaq is the CEO of Marktechpost Media Inc.. As a visionary entrepreneur and engineer, Asif is committed to harnessing the potential of Artificial Intelligence for social good. His most recent endeavor is the launch of an Artificial Intelligence Media Platform, Marktechpost, which stands out for its in-depth coverage of machine learning and deep learning news that is both technically sound and easily understandable by a wide audience. The platform boasts of over 2 million monthly views, illustrating its popularity among audiences.
