Rohan Paul@rohanpaul_ai · X微软发布了 MAI-Thinking-1，这是一款采用 MoE 架构的模型，拥有 35B 活跃参数和 1T 总参数。该模型从零开始在 30T tokens 上完成预训练，且未使用第三方模型蒸馏。微软称其迭代优化流程为“爬山机器”。在基准测试中，该模型于 AIME 2025 获得 97.0%，在 LiveCodeBench v6 获得 87.7%，在 SWE-Bench Pro 获得 52.8% 的成绩。
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.