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Microsoft Build 2026 (June 2–3, Fort Mason, San Francisco) shipped MAI-Code-1-Flash into GitHub Copilot's model picker across Free, Pro, Pro+, and Max plans. The model posts a 51.2% pass rate on SWE-Bench Pro versus Claude Haiku 4.5's 35.2%, and solves harder problems with up to 60% fewer tokens on SWE-Bench Verified (per Microsoft AI). In the same week, GitHub took the Copilot SDK to GA with stable API, Rust, and Java support; moved Copilot Workspace out of beta; switched billing to AI Credits (live June 1); and announced Project Polaris to replace GPT-4 Turbo by August. Why it matters. Five model options in one picker means five wrong defaults. MAI-Code-1-Flash is the right pick for fast iteration loops. Claude Sonnet 4.6 still wins on long-context refactors. We built a task-by-task matrix so you can set the right model for each job without burning credits on the wrong one.
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