Codestral

We introduce Codestral, our first-ever code model. Codestral is an open-weight generative AI model explicitly designed for code generation tasks. It helps developers write and interact with code through a shared instruction and completion API endpoint. As it masters code and English, it can be used to design advanced AI applications for software developers.

Codestral is trained on a diverse dataset of 80+ programming languages, including the most popular ones, such as Python, Java, C, C++, JavaScript, and Bash. It also performs well on more specific ones like Swift and Fortran. This broad language base ensures Codestral can assist developers in various coding environments and projects.

Codestral saves developers time and effort: it can complete coding functions, write tests, and complete any partial code using a fill-in-the-middle mechanism. Interacting with Codestral will help level up the developer's coding game and reduce the risk of errors and bugs.

Codestral is a 22B open-weight model licensed under the new Mistral AI Non-Production License , which means that you can use it for research and testing purposes. Codestral can be downloaded on HuggingFace .

"As a researcher at the company that created the first developer focused GenAI tool, I've had the pleasure of integrating Mistal's new code model into our chat product. I am thoroughly impressed by its performance. Despite its relatively compact size, it delivers results on par with much larger models we offer to customers. We tested several key features, including code generation, test generation, documentation, onboarding processes, and more. In each case, the model exceeded our expectations. The speed and accuracy of the model will significantly impact our product's efficiency vs the previous Mistral model, allowing us to provide quick and precise assistance to our users. This model stands out as a powerful tool among the models we support, and I highly recommend it to others seeking high-quality performance."

Performance. As a 22B model, Codestral sets a new standard on the performance/latency space for code generation compared to previous models used for coding.

Figure 1: With its larger context window of 32k (compared to 4k, 8k or 16k for competitors), Codestral outperforms all other models in RepoBench, a long-range eval for code generation..

We compare Codestral to existing code-specific models with higher hardware requirements.