Microsoft just made its most significant bet yet on building AI from scratch. At Build 2026, the company's MAI lab unveiled seven new models spanning every major modality: reasoning, coding, image generation, transcription, and voice. The headline is not just the models themselves , it is the philosophy behind them. Every single one was trained from the ground up on clean, traceable data, with zero distillation from third-party models like GPT or Claude.
The new MAI model family forms a multimodal ecosystem designed to work across the kinds of tasks that matter in the real world. And unlike most of the industry's recent launches, Microsoft does not distill from other labs and does not rely on unlicensed or opaque data , every component of the system, from architecture to training pipeline to post-training, was built in-house.
The flagship: a reasoning model that punches above its weight
MAI-Thinking-1 is a 35B-active, approximately 1-trillion-total-parameter sparse Mixture of Experts model , a smaller inference footprint than much larger models. Despite this, it is toe-to-toe with Claude Opus 4.6 on SWE-Bench Pro. Mixture of Experts (MoE) is an architecture where only a subset of the model's parameters are active for any given input, making it much cheaper to run than a dense model of equivalent total size.
MAI-Thinking-1 matches leading models on key software engineering benchmarks, demonstrates advanced mathematical reasoning capabilities, and is preferred to Sonnet 4.6 in blind human side-by-side evaluations. On math, it reaches 97.0% on AIME 2025 and 94.5% on AIME 2026, showing strong mathematical and scientific reasoning for its weight class.
MAI-Thinking-1 supports long context with a 256k token window , enough to fit a 600-page document , along with function calling and compatibility with the widely used Chat Completions API. It is available in private preview on Microsoft Foundry today, with a public preview on the MAI Playground coming soon.
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