Mistral Releases Devstral 61b64 an Open-Source Agentic Coding AI Model That Outperforms GPT-4.1 Mini

Devstral is fine-tuned from Mistral-Small-3.1 and has a context window of up to 1,28,000 tokens. 1q643n

Written by Siddharth Suvarna | Updated: 22 May 2025 16:15 IST

Mistral Releases Devstral, an Open-Source Agentic Coding AI Model That Outperforms GPT-4.1 Mini

Photo Credit: Unsplash/Solen Feyissa 1x452c

The Devstral coding agent can be run both locally as well as via Mistral’s API

Highlights

Devstral was built as a collaboration between Mistral and All Hands AI
The coding model scores 46.8 percent on the SWE-Bench Verified benchmark
Mistral’s open-source model is available under an Apache 2.0 licence

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Mistral released a new coding-focused artificial intelligence (AI) model on Wednesday. Dubbed Devstral, it is an open-source coding agent that can perform software development tasks. The Paris-based AI firm says that, unlike other open software engineering (SWE) agents, this model can solve real-world software engineering problems and write contextualised code in a codebase. The company claimed that the AI model ranked at the top of the SWE-Verified benchmark based on internal tests. Notably, Mistral built the AI model in collaboration with All Hands AI.

Mistral's Devstral Coding Agent Is Claimed to Offer Practical Coding Capabilities 365q

In a newsroom post, the French AI firm announced the coding and detailed its capabilities. In the last month, major AI players have been focusing on bringing AI-powered coding agents to the market. OpenAI introduced Codex, Microsoft unveiled the GitHub Copilot coding agent, and Google made Jules available as a public beta. Now, Mistral has also ed these companies with Devstral.

Mistral said that while existing open-source large language models (LLMs) are capable of performing isolated coding tasks such as writing standalone functions or code completion, they struggle when it comes to writing contextual code in a large codebase. The company added that this leads to issues when AI agents have to identify relationships between disparate components and also identify subtle bugs.

Mistral’s New Medium 3 AI Model Is Optimised for Performance and Cost

The company believes Devstral solves this problem with its ability to contextualise coding tasks with the database and existing frameworks. Based on internal testing, it scored 46.8 percent on the SWE-Verified benchmark, ranking in the top position. It also outperformed larger open-source models such as Qwen 3 and DeepSeek V3, as well as proprietary models such as OpenAI's GPT-4.1-mini and Anthropic's Claude 3.5 Haiku.

Coming to the architecture, Devstral is fine-tuned from the Mistral-Small-3.1 AI model and has a context window of up to 1,28,000 tokens. It is a text-only model as it comes without the vision encoder that was equipped in the Small-3.1. Notably, Devstral can use tools to explore codebases, edit multiple files, and power other SWE agents.

Mistral says that Devstral is a lightweight model that can run on a single Nvidia RTX 4090 GPU or a Mac with 32GB RAM. Due to this, it can be deployed locally and run entirely on-device. Those who wish to the model can access it from Hugging Face, Ollama, Kaggle, Unsloth, and LM Studio. It is available with a permissive Apache 2.0 licence that allows for both academic and commercial usages.

Additionally, it can also be used as an application programming interface (API). Mistral has listed the AI agent under the name devstral-small-2505, and it costs $0.1 (roughly Rs. 8.6) per million of input tokens and $0.3 (roughly Rs. 25) per million of output tokens.

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Akash Dutta Email Akash Dutta

Akash Dutta is a Senior Sub Editor at Gadgets 360. He is particularly interested in the social impact of technological developments and loves reading about emerging fields such as AI, metaverse, and fediverse. In his free time, he can be seen ing his favourite football club - Chelsea, watching movies and anime, and sharing ionate opinions on food. More