MiMo-VL Technical Report
Authors: name: Xiaomi LLM-Core Team; name: Zihao Yue; name: Zhenru Lin; name: Yifan Song; name: Weikun Wang; name: Shuhuai Ren; name: Shuhao Gu; name: Shicheng Li; name: Peidian Li; name: Liang Zhao; name: Lei Li; name: Kainan Bao; name: Hao Tian; name: Hailin Zhang; name: Gang Wang; name: Dawei Zhu; name: Cici; name: Chenhong He; name: Bowen Ye; name: Bowen Shen; name: Zihan Zhang; name: Zihan Jiang; name: Zhixian Zheng; name: Zhichao Song; name: Zhenbo Luo; name: Yue Yu; name: Yudong Wang; name: Yuanyuan Tian; name: Yu Tu; name: Yihan Yan; name: Yi Huang; name: Xu Wang; name: Xinzhe Xu; name: Xingchen Song; name: Xing Zhang; name: Xing Yong; name: Xin Zhang; name: Xiangwei Deng; name: Wenyu Yang; name: Wenhan Ma; name: Weiwei Lv; name: Weiji Zhuang; name: Wei Liu; name: Sirui Deng; name: Shuo Liu; name: Shimao Chen; name: Shihua Yu; name: Shaohui Liu; name: Shande Wang; name: Rui Ma; name: Qiantong Wang; name: Peng Wang; name: Nuo Chen; name: Menghang Zhu; name: Kangyang Zhou; name: Kang Zhou; name: Kai Fang; name: Jun Shi; name: Jinhao Dong; name: Jiebao Xiao; name: Jiaming Xu; name: Huaqiu Liu; name: Hongshen Xu; name: Heng Qu; name: Haochen Zhao; name: Hanglong Lv; name: Guoan Wang; name: Duo Zhang; name: Dong Zhang; name: Di Zhang; name: Chong Ma; name: Chang Liu; name: Can Cai; name: Bingquan Xia
Published: 2025-06-04 04:32:54

Abstract: We open-source MiMo-VL-7B-SFT and MiMo-VL-7B-RL, two powerful vision-language
models delivering state-of-the-art performance in both general visual
understanding and multimodal reasoning. MiMo-VL-7B-RL outperforms Qwen2.5-VL-7B
on 35 out of 40 evaluated tasks, and scores 59.4 on OlympiadBench, surpassing
models with up to 78B parameters. For GUI grounding applications, it sets a new
standard with 56.1 on OSWorld-G, even outperforming specialized models such as
UI-TARS. Our training combines four-stage pre-training (2.4 trillion tokens)
with Mixed On-policy Reinforcement Learning (MORL) integrating diverse reward
signals. We identify the importance of incorporating high-quality reasoning
data with long Chain-of-Thought into pre-training stages, and the benefits of
mixed RL despite challenges in simultaneous multi-domain optimization. We also
contribute a comprehensive evaluation suite covering 50+ tasks to promote
reproducibility and advance the field. The model checkpoints and full
evaluation suite are available at https://github.com/XiaomiMiMo/MiMo-VL.