I remember back in the GPT-4 era, many custom models appeared, specifically "tuned" for programming. There were even separate models for Python. Phind.com was doing cool stuff. Then it all somehow subsided, and most universal models became good at writing code anyway.

https://windsurf.com/blog/windsurf-wave-9-swe-1
Windsurf recently released their SWE-1 models, but I think this is more of a step to reduce external API costs.

The Mistral company still provides API access to the closed Codestral model, last updated January 2025.

And here we have a new turn, now models are being configured for background independent coding of a range of tasks from a git repository. OpenAI has just re-released Codex, now based on o3. Github has updated its agent, adding a background work function.

https://mistral.ai/news/devstral
Mistral's answer is the Devstral model, developed jointly with All-hands (an open-source clone of the AI developer Devin). Unlike Codestral, the license here is Apache 2.0, meaning free use and modification. The model is also available via API under the name devstral-small-2505.

What the model does better:

• Parses large repositories
• Finds connections between components
• Scans code for errors
• Is trained to solve real problems from GitHub

According to All Hands AI 🙌, Devstral outperforms significantly larger models such as Deepseek-V3-0324 (671B) and Qwen3 232B-A22B. At the same time, Devstral is light enough to run on a single RTX 4090 or a Mac with 32 GB of RAM, making it an ideal choice for background local use.