MAI-Code-1.1-Flash: Better, faster, at a quarter of the cost (2 minute read)

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Summary

Microsoft introduces MAI-Code-1.1-Flash, a faster, cheaper, and more token-efficient coding model now in production in GitHub Copilot, with improvements in CLI and .NET tasks.

MAI-Code-1.1-Flash produces higher quality code at 25% greater token efficiency and at a quarter of the cost compared to the previous model launched in June. This was achieved by optimizing for real-world use across hundreds of thousands of reinforcement-learning environments in GitHub Copilot. MAI-Code-1.1-Flash shows a 22% improvement on Terminal-Bench 2.1 in GitHub Copilot CLI and a 15% improvement on .NET tasks. It is now available in GitHub Copilot.
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# MAI-Code-1.1-Flash: Better, faster, at a quarter of the cost | Microsoft AI Source: [https://microsoft.ai/news/mai-code-1-1-flash-br-better-faster-at-a-quarter-of-the-cost/](https://microsoft.ai/news/mai-code-1-1-flash-br-better-faster-at-a-quarter-of-the-cost/) Models ![Large white curly braces on a green background with blurred text. In the center, it says “MAI-Code-1.1-Flash 25% Greater Token Efficiency A Quarter of the Cost.” Subtle code text is visible in the background.](https://microsoft.ai/wp-content/uploads/2026/08/MAI_Code_1_1_Flash_Header-1.webp) MAI\-Code\-1\.1\-Flash produces higher quality code, at 25% greater token efficiency, and at**a quarter of the cost**compared to the model we launched in June at Microsoft Build\. This small, efficient, coding workhorse is now in production in GitHub Copilot\. We learned from developer feedback that CLI tasks and \.NET performance mattered, so that’s where we focused\. The result: a**22% improvement on Terminal\-Bench 2\.1**in GitHub Copilot CLI and a**15% improvement on \.NET tasks**\. Benchmarks are useful guides but production is where the rubber meets the road\. Most importantly, code survival rose 4% and**return visits increased 9%**\. 1\.1 is also dramatically more efficient\. In GitHub Copilot tokens stream**25% faster**and the model uses**25% fewer tokens**to complete a task\. That means faster answers, less waiting, and more useful work from every token—not simply a bigger model with a bigger bill\. Better training and serving efficiency let us offer a stronger, faster model at one quarter of the price of 1\.0—and pass those savings reliably to customers\. We achieved this by optimizing for real\-world use across more than hundreds of thousands of reinforcement\-learning environments in GitHub Copilot\. The loop is simple: ship, learn, improve, repeat\. That’s the MAI hill climbing machine\. ## **Help shape future improvements** Try MAI\-Code\-1\.1\-Flash today in[GitHub Copilot](https://github.com/features/copilot), then tell us what needs improving by opening an issue[here](https://github.com/microsoft/MAI-Code)\. ## Build the Future With Us We’re a lean, talent\-dense team of explorers, researchers, and full\-stack engineers\. We move fast, sweat the details, and operate at frontier scale with a roadmap to build the world’s most powerful AI models\. Most importantly, we’re united by the belief that doing this right is the only way to do it at all\. If our mission resonates with you, we’d love to talk\. [Explore all jobs](https://microsoft.ai/careers) ## Related Stories

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