Microsoft unveiled MAI-Thinking-1.

So Microsoft now has a full in-house pipeline for building stronger reasoning models again and again.

Microsoft calls this system a "hill-climbing machine," meaning it keeps improving the data, training setup, rewards, safety tests, and evaluations as one connected process.

Strong for its size, including 97.0% on AIME 2025, 87.7% on LiveCodeBench v6, and 52.8% on SWE-Bench Pro.

MAI-Thinking-1 is the first model from that process, using 35B active parameters inside a 1T total parameter mixture-of-experts model, where only part of the model runs for each token.

The base model was trained from scratch on 30T mostly human-generated tokens, with Microsoft saying it avoided third-party model distillation during pre-training.

After that, the team used reinforcement learning, which means the model practiced tasks and improved from feedback, to teach math reasoning, coding, tool use, helpfulness, and safety.