
Microsoft AI has released the MAI-Code-1-Flash model for GitHub Copilot Business and Enterprise users. This coding model is optimized for fast, low-latency responses, catering to high-volume and iterative coding workflows. It is available under usage-based billing, and administrators must enable it in Copilot settings. This release aims to enhance coding efficiency for enterprise users, aligning with GitHub's strategy to provide tailored solutions for business environments.
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GitHub Changelog · May 19, 2026 · Same story
This release quietly cements llama.cpp as the universal inference runtime by finally supporting NVIDIA's latest CUDA 13 stack alongside AMD's ROCm 10.0. The inclusion of native builds for Linux arm64 with Snapdragon chips, covering CPU, Adreno GPU, and Hexagon NPU, signals a serious push into mobile edge deployment. While Apple Silicon KleidiAI is disabled in this specific build, the broader hardware coverage means developers no longer need to compile from source for most modern accelerators. It’s less about new features and more about removing friction for anyone running local models on bleeding-edge or diverse hardware.
© The Verge AIMatt Wolfe · June 10, 2026 · Related
GitHub Changelog · August 11, 2026 · Same story
Matt Wolfe · August 14, 2026 · Same story
MAI-Code-1-Flash expands to more Copilot platforms
3 developments
Apple is finally unlocking its AI suite for Chinese users with the iOS 27.3 beta, marking a significant regulatory milestone after months of approval delays. The rollout relies on Alibaba’s Qwen model rather than OpenAI, integrating features like notification summaries and visual intelligence directly into the OS. By sidestepping the new Siri in favor of established text and image tools, Apple is prioritizing immediate utility over the full generative experience. This move effectively brings Apple’s AI capabilities to a massive new market, albeit with localized constraints that distinguish it from the global release.