Mistral AI just launched ‘Codestral’, its own competitor to Code Llama and GitHub Copilot — and it’s fluent in over 80 programming languages
The launch of Codestral marks Mistral AI’s first foray into the coding assistant market, pitting it against major platforms like GitHub Copilot and Code Llama
Mistral AI has unveiled the launch of ‘Codestral’, its first generative AI coding assistant designed specifically to support developers.
The Microsoft-backed French startup said the new AI tool has been trained on over 80 programming languages, including Java, Python, JavaScript, and C++.
Codestral “also performs well” on more specific programming languages, Mistral said, including Swift and Fortran.
“This broad language base ensures Codestral can assist developers in various coding environments and projects,” the firm said in a blog post.
Like other code generation tools on the market, such as Code Llama, GitHub Copilot, or Amazon Q Developer (formerly CodeWhisperer) Mistral’s tool enables developers to write and generate code.
The tool can complete coding functions, write tests, and complete “any partial code using a fill-in-the-middle mechanism”, the company said.
“Interacting with Codestral will help level up the developer’s coding game and reduce the risk of error and bugs.”
The new model also boasts impressive performance metrics, coming in as a 22B parameter model. Mistral said this sets a new standard on performance and latency for code generation compared to other models currently available on the market, including the Code Llama 70B model.
Is Mistral AI's Codestral model open source?
Mistral described Codestral as an “open-weight” generative AI model in its blog post, meaning it’s not strictly ‘open source’ by most definitions.
This has been a contentious topic in the AI space in recent months, with some industry stakeholders noting that major firms such as Meta, for example, have framed their models and tools as open source while still restricting commercial use.
Codestral is licensed under the new Mistral AI Non-Production License, which the company said can be used for “research and testing purposes”. This means that it can’t be used openly for commercial purposes.
“This license allows developers to use our technology for non-commercial purposes and to support research work,” the firm said in a blog post outlining the licensing terms. “It ensures that those who build a business based on our work do so in a fair and sustainable way for all parties.”
Mistral said that this new license “strikes the right balance between our commitment to openness principles and our responsibility to grow our business”.
The firm added that it will still continue releasing models and code under Apache 2.0 licensing.
Codestral has some serious competition
Codestral’s launch marks Mistral’s first serious foray into the coding assistant space, pitting it against a raft of major industry heavyweights such as GitHub, AWS, and Meta.
Since the advent of generative AI in late 2022, one of the leading use cases for the technology touted by providers has been support for developers to improve productivity and alleviate strain placed on development teams.
Research on the topic shows that developers are keen on these tools, with a study from GitHub last year revealing that users can complete tasks 55% faster using an AI assistant.
The use of AI assistants also helps improve workflows and reduces developer toil, the study found, further improving overall productivity.
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Research has shown some major pitfalls, however. A study from GitClear earlier this year found “disconcerting trends” in terms of reliability and accuracy.
GitClear examined more than 150 million lines of code written between January 2020 and December 2023 to see if it could spot code quality differences as a result of AI coding assistants. The results were far from exemplary and uncovered a sharp increase in ‘code churn’.
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