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arXiv · 2507.20534

Kimi K2: Open Agentic Intelligence

Kimi Team·Yifan Bai·Yiping Bao·Y. Charles·Cheng Chen·Guanduo Chen·Haiting Chen·Huarong Chen·Jiahao Chen·Ningxin Chen·Ruijue Chen·Yanru Chen·Yuankun Chen·Yutian Chen·Zhuofu Chen·Jialei Cui·Hao Ding·Mengnan Dong·Angang Du·Chenzhuang Du·Dikang Du·Yulun Du·Yu Fan·Yichen Feng·Kelin Fu·Bofei Gao·Chenxiao Gao·Hongcheng Gao·Peizhong Gao·Tong Gao·Yuyao Ge·Shangyi Geng·Qizheng Gu·Xinran Gu·Longyu Guan·Haiqing Guo·Jianhang Guo·Xiaoru Hao·Tianhong He·Weiran He·Wenyang He·Yunjia He·Chao Hong·Hao Hu·Yangyang Hu·Zhenxing Hu·Weixiao Huang·Zhiqi Huang·Zihao Huang·Tao Jiang·Zhejun Jiang·Xinyi Jin·Yongsheng Kang·Guokun Lai·Cheng Li·Fang Li·Haoyang Li·Ming Li·Wentao Li·Yang Li·Yanhao Li·Yiwei Li·Zhaowei Li·Zheming Li·Hongzhan Lin·Xiaohan Lin·Zongyu Lin·Chengyin Liu·Chenyu Liu·Hongzhang Liu·Jingyuan Liu·Junqi Liu·Liang Liu·Shaowei Liu·T. Y. Liu·Tianwei Liu·Weizhou Liu·Yangyang Liu·Yibo Liu·Yiping Liu·Yue Liu·Zhengying Liu·Enzhe Lu·Haoyu Lu·Lijun Lu·Yashuo Luo·Shengling Ma·Xinyu Ma·Yingwei Ma·Shaoguang Mao·Jie Mei·Xin Men·Yibo Miao·Siyuan Pan·Yebo Peng·Ruoyu Qin·Zeyu Qin·Bowen Qu·Zeyu Shang·Lidong Shi
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Abstract

We introduce Kimi K2, a Mixture-of-Experts (MoE) large language model with 32 billion activated parameters and 1 trillion total parameters. We propose the MuonClip optimizer, which improves upon Muon with a novel QK-clip technique to address training instability while enjoying the advanced token efficiency of Muon. Based on MuonClip, K2 was pre-trained on 15.5 trillion tokens with zero loss spike. During post-training, K2 undergoes a multi-stage post-training process, highlighted by a large-scale agentic data synthesis pipeline and a joint reinforcement learning (RL) stage, where the model improves its capabilities through interactions with real and synthetic environments. Kimi K2 achieves state-of-the-art performance among open-source non-thinking models, with strengths in agentic capabilities. Notably, K2 obtains 66.1 on Tau2-Bench, 76.5 on ACEBench (En), 65.8 on SWE-Bench Verified, and 47.3 on SWE-Bench Multilingual -- surpassing most open and closed-sourced baselines in non-thinking settings. It also exhibits strong capabilities in coding, mathematics, and reasoning tasks, with a score of 53.7 on LiveCodeBench v6, 49.5 on AIME 2025, 75.1 on GPQA-Diamond, and 27.1 on OJBench, all without extended thinking. These results position Kimi K2 as one of the most capable open-source large language models to date, particularly in software engineering and agentic tasks. We release our base and post-trained model checkpoints to facilitate future research and applications of agentic intelligence.

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Kimi Team, Yifan Bai, Yiping Bao, Y. Charles, Cheng Chen, Guanduo Chen, Haiting Chen, Huarong Chen, Jiahao Chen, Ningxin Chen, Ruijue Chen, Yanru Chen, Yuankun Chen, Yutian Chen, Zhuofu Chen, Jialei Cui, Hao Ding, Mengnan Dong, Angang Du, Chenzhuang Du, Dikang Du, Yulun Du, Yu Fan, Yichen Feng, Kelin Fu, Bofei Gao, Chenxiao Gao, Hongcheng Gao, Peizhong Gao, Tong Gao, Yuyao Ge, Shangyi Geng, Qizheng Gu, Xinran Gu, Longyu Guan, Haiqing Guo, Jianhang Guo, Xiaoru Hao, Tianhong He, Weiran He, Wenyang He, Yunjia He, Chao Hong, Hao Hu, Yangyang Hu, Zhenxing Hu, Weixiao Huang, Zhiqi Huang, Zihao Huang, Tao Jiang, Zhejun Jiang, Xinyi Jin, Yongsheng Kang, Guokun Lai, Cheng Li, Fang Li, Haoyang Li, Ming Li, Wentao Li, Yang Li, Yanhao Li, Yiwei Li, Zhaowei Li, Zheming Li, Hongzhan Lin, Xiaohan Lin, Zongyu Lin, Chengyin Liu, Chenyu Liu, Hongzhang Liu, Jingyuan Liu, Junqi Liu, Liang Liu, Shaowei Liu, T. Y. Liu, Tianwei Liu, Weizhou Liu, Yangyang Liu, Yibo Liu, Yiping Liu, Yue Liu, Zhengying Liu, Enzhe Lu, Haoyu Lu, Lijun Lu, Yashuo Luo, Shengling Ma, Xinyu Ma, Yingwei Ma, Shaoguang Mao, Jie Mei, Xin Men, Yibo Miao, Siyuan Pan, Yebo Peng, Ruoyu Qin, Zeyu Qin, Bowen Qu, Zeyu Shang, Lidong Shi. 2025-07-28. Kimi K2: Open Agentic Intelligence. https://arxiv.org/abs/2507.20534

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