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

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.