Microsoft just completed pre-training MAI-Base-2, a massive MoE model with 80 billion active and 2.8 trillion total parameters. Trained on 16k GB200 GPUs in 38 days without distillation, it outperforms tested open-weight models and runs 4x to 12x more FLOPs-efficient than DeepSeek-V4-Pro-Base. Why it matters: Microsoft is proving it can build frontier models in-house to license directly to enterprise partners.
Microsoft is quietly swapping out top-tier models from OpenAI and Anthropic across Excel and Outlook, replacing them with its own in-house MAI models to cut soaring bills. Microsoft AI chief Mustafa Suleyman said Anthropic is "extremely expensive" and aims to eliminate that spend completely. The change handles tens of thousands of weekly prompts, marking a clear pivot toward cheaper, self-reliant infrastructure.
Microsoft just rolled out seven in-house MAI models covering reasoning, coding, vision, and speech, all built from scratch on clean data without third-party distillation. The drop includes MAI-Thinking-1, a lightweight coding model for GitHub Copilot, and an enterprise tuning workflow called Frontier Tuning. Why it matters: Microsoft is aggressively engineering full-stack independence across its own silicon and software.
Microsoft is preparing to unveil a wave of major updates at Build, led by its first in-house reasoning model, MAI-Thinking-1. The company is also set to showcase a distraction-free Windows 11 developer experience and a unified Copilot super app. Why it matters: Microsoft is leaning heavily into local AI compute on Windows to win back developer trust.
