Microsoft's MAI-Code-1.1-Flash Hits GitHub Copilot at 73% Lower Cost
MAI-Code-1.1-Flash lands in GitHub Copilot with native vision, 25% better token efficiency, and a 73% price cut over its predecessor
- MAI-Code-1.1-Flash is now rolling out in GitHub Copilot across all tiers and surfaces.
- Costs 73% less than its predecessor (0.25x premium request multiplier for annual subscribers).
- Adds native vision support for image understanding, a first for the MAI-Code line.
- 25% faster token streaming, 25% fewer tokens per task, 22% better CLI performance, 15% better on .NET.
- Trained directly on GitHub Copilot production harnesses using reinforcement learning across hundreds of thousands of real-world environments.
- Enterprise and Business admins must manually enable the policy in Copilot settings; it is off by default.
Microsoft's MAI-Code-1.1-Flash is now rolling out inside GitHub Copilot, and the headline number is hard to ignore: it costs 73% less than the model it replaces while actually being faster and more capable. That's a rare combination in AI, where capability improvements almost always come with a price hike.
What changed from 1.0 to 1.1
MAI-Code-1.1-Flash is Microsoft's latest small-tier coding model, building on MAI-Code-1-Flash with native vision support for image understanding and improvements across coding quality, instruction following, tool use, and performance. The vision addition is new territory for the MAI-Code line, letting the model reason over screenshots, diagrams, and UI mockups alongside code.
The efficiency story is just as compelling as the feature additions. 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 launched in June. In practical terms, better training and serving efficiency let Microsoft offer a stronger, faster model at one quarter of the price of 1.0, achieved by optimizing for real-world use across hundreds of thousands of reinforcement-learning environments in GitHub Copilot.
The numbers that matter
Microsoft published concrete benchmark improvements driven by developer feedback on what actually mattered in daily use:
- 22% improvement on Terminal-Bench 2.1