What is Codestral? Price, Key Features, and Limitations

A few months ago, Mistral AI launched Codestral, a generative AI model for code generation tasks. The model was created to enhance the abilities of developers and make coding accessible to all. It offers advanced features for writing and conversing with code. 

Codestral is the first code assistance model from Mistral AI. It was developed with the aim of assisting programmers in their coding tasks. Announcing the release in a blog post, Mistral AI says that Codestral can understand and generate code for more than 80 programming languages. 

This article will explore this impressive code model, its features, limitations, pricing, and more.

Mistral AI introduces Codestral, its First-Ever Code Model

What is Codestral?

As per the official blog post, “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.”

Arthur Mensch Net Worth: Mistral AI CEO and Co-Founder

Key Features

• Fluency in Over 80 Programming Languages

Codestral can understand more than 80 programming languages. This includes widely used ones like Python, Java, C, C++, JavaScript, and Bash alongside specialized options such as Swift and Fortran among others. Such extensive coverage makes Codestral useful for many kinds of projects and coding settings.

• Advanced Code Generation

Codestral is good at automating tasks such as filling in the missing parts of code, generating tests automatically, and doing what is called “filling in the middle” for coding sections that are not complete. This feature comes in handy when dealing with intricate codebases or languages you are not yet familiar with. 

• Performance and Efficiency

With a 22 billion parameter model, Codestral is the new standard of code generation and latency. The model’s bigger context window of 32k tokens shows better results in dealing with long-range code completion tasks compared to other models. It is highly effective for managing extensive codebases.

• Open-Weight Model

The open-weight feature of Codestral promotes cooperation and creativity in the AI field. Developers or researchers can try out the model, adjust it for particular jobs, and participate in its continual progress. 

What is Amazon Bedrock? AWS Generative AI Tool Powered by Mistral

Codestral Pricing

Codestral is available under the Mistral AI Non-Production License for research and testing purposes, making it accessible for non-commercial use. For commercial use, Mistral AI offers licenses on demand.  You can access Codestral via a special endpoint free of charge in an eight-week beta phase, with your API keys and no organization rate limits included. 

Codestral is integrated into Mistral AI’s La Plateforme for more extensive use cases, where queries are billed per token.

Mistral and Microsoft accelerate AI innovation with the launch of Mistral Large on Azure

Comparison with Other Models

The 32k token context window of Codestral brings excellent results for long-range code completion tasks. It shows strong performance in benchmarks such as HumanEval for Python and other languages, sometimes even passing bigger models like Llama 3 70B and DeepSeek Coder 33B. 

Although it may be smaller compared to those larger models, the efficiency and precision of Codestral make it a serious contender among code generation solutions.

Codestral Limitations

Despite its impressive performance, Codestral has its shortcomings.

• Benchmark Performance

Although Codestral demonstrates good results in certain tests, actual performance may differ depending on the difficulty level of the task and the programming language employed. Before completely depending on Codestral for production, it is advised to conduct extensive tests across various environments.

• Limited Context Window

While Codestral claims to have a context window of 32k tokens, some situations might demand an even bigger context for comprehending complicated codebases completely. This drawback can impact its functioning in highly intricate projects.

• Potential Bias

Like all AI models that are trained on existing code, Codestral could also have biases from the training data. This might cause it to produce code that unintentionally continues unwanted patterns or methods, requiring careful monitoring and examination.

• Evolving Technology

Codestral is still a relatively new model. Its effectiveness in different applications may vary as more development and refinement take place in the future.

Mistral Drops OpenAI Language Model via Torrent Link

The Bottom Line

Codestral is a big step forward in using AI to generate code. It offers developers a powerful tool for automating coding work and enhancing their productivity. Although there are different areas where this model shows potential, it has its own shortcomings as well.