Back in June, Microsoft first revealed MAI-Code-1, an inference-efficient coding model tuned for GitHub Copilot workloads. Since then, the Flash variant of MAI-Code-1 has been made available in GitHub Copilot as an alternative to models from OpenAI and Anthropic.
While the pricing and efficiency of MAI-Code-1-Flash looked competitive at the time of its announcement, it was quickly overshadowed by affordable and powerful Chinese models such as GLM-5.2 and Kimi K3, as well as OpenAI’s GPT-5.6 Luna.
Microsoft has now announced MAI-Code-1.1-Flash, an upgraded version that delivers better coding performance while significantly reducing cost and token usage. According to Microsoft, the new model performs 22% better on Terminal-Bench 2.1 when used through the GitHub Copilot CLI and delivers a 15% improvement on .NET tasks.
Microsoft also claims that tokens stream 25% faster while the model uses 25% fewer tokens to complete the same task. Improvements to training and serving efficiency have allowed Microsoft to offer MAI-Code-1.1-Flash at one-quarter of the price of the original model. This model is charged at a 0.25x premium request multiplier for annual Copilot subscribers.
As per the GitHub Copilot pricing table, MAI-Code-1.1-Flash costs $0.20 per 1M input tokens, $0.02 per 1M cached input tokens, and $1.20 per 1M output tokens. This is dramatically lower than MAI-Code-1-Flash, which costs $0.75 / $0.075 / $4.50 per 1M tokens.
Beyond coding improvements, MAI-Code-1.1-Flash adds native vision support for understanding images.
MAI-Code-1.1-Flash is now rolling out across GitHub Copilot, including VS Code, Visual Studio, JetBrains IDEs, Copilot CLI, GitHub Mobile, and other supported experiences. Free and Student users can access it through automatic model selection, while paid users can manually select it.
With the upgraded model now available, GitHub will retire MAI-Code-1-Flash across all Copilot experiences on September 10, 2026.
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Автор – Pradeep Viswanathan
