Xiaomi open-sources MiMo-V2.6 models after scaling reinforcement learning

Xiaomi released and open-sourced the MiMo-V2.6 series, including the native multimodal MiMo-V2.6-Pro and MiMo-V2.6-Flash models, plus MiMo-V2.6-Distill-Qwen-9B and reinforcement-learning research resources. Xiaomi said MiMo-V2.6-Pro scored 46 on the Artificial Analysis Intelligence Index, ahead of Kimi K3 at 44 and GLM-5.3 at 45, making it the highest-ranked open-weight model on the index, while leading closed-source models scored 53. The two models completed 30 reinforcement-learning steps in less than six days using about 750,000 trajectories, at reported costs of $2.62 million for Pro and $850,000 for Flash, and the release adds 3D spatial reasoning, multimodal perception, computer-use capabilities and a desktop client.

Xiaomi has released and open-sourced the MiMo-V2.6 series, including the native multimodal MiMo-V2.6-Pro and MiMo-V2.6-Flash models. Xiaomi also released MiMo-V2.6-Distill-Qwen-9B and research resources for reinforcement learning. MiMo-V2.6-Pro scored 46 on the Artificial Analysis Intelligence Index, ahead of Kimi K3 at 44 and GLM-5.3 at 45, according to Xiaomi’s cited comparison. The company described it as the highest-ranked open-weight model on the index, while noting that leading closed-source models scored 53. The two models completed 30 reinforcement-learning steps in less than six days, using about 750,000 trajectories at reported costs of $2.62 million for Pro and $850,000 for Flash. The release also adds 3D spatial reasoning, multimodal perception, computer-use capabilities and a desktop client. Xiaomi MiMo https://mimo.mi.com/docs/zh-CN/news/latest/v2-6 , in Chinese