Kling-Omni Technical Report
Authors: name: Kling Team; name: Jialu Chen; name: Yuanzheng Ci; name: Xiangyu Du; name: Zipeng Feng; name: Kun Gai; name: Sainan Guo; name: Feng Han; name: Jingbin He; name: Kang He; name: Xiao Hu; name: Xiaohua Hu; name: Boyuan Jiang; name: Fangyuan Kong; name: Hang Li; name: Jie Li; name: Qingyu Li; name: Shen Li; name: Xiaohan Li; name: Yan Li; name: Jiajun Liang; name: Borui Liao; name: Yiqiao Liao; name: Weihong Lin; name: Quande Liu; name: Xiaokun Liu; name: Yilun Liu; name: Yuliang Liu; name: Shun Lu; name: Hangyu Mao; name: Yunyao Mao; name: Haodong Ouyang; name: Wenyu Qin; name: Wanqi Shi; name: Xiaoyu Shi; name: Lianghao Su; name: Haozhi Sun; name: Peiqin Sun; name: Pengfei Wan; name: Chao Wang; name: Chenyu Wang; name: Meng Wang; name: Qiulin Wang; name: Runqi Wang; name: Xintao Wang; name: Xuebo Wang; name: Zekun Wang; name: Min Wei; name: Tiancheng Wen; name: Guohao Wu; name: Xiaoshi Wu; name: Zhenhua Wu; name: Da Xie; name: Yingtong Xiong; name: Yulong Xu; name: Sile Yang; name: Zikang Yang; name: Weicai Ye; name: Ziyang Yuan; name: Shenglong Zhang; name: Shuaiyu Zhang; name: Yuanxing Zhang; name: Yufan Zhang; name: Wenzheng Zhao; name: Ruiliang Zhou; name: Yan Zhou; name: Guosheng Zhu; name: Yongjie Zhu
Published: 2025-12-18 17:08:12

Abstract: We present Kling-Omni, a generalist generative framework designed to synthesize high-fidelity videos directly from multimodal visual language inputs. Adopting an end-to-end perspective, Kling-Omni bridges the functional separation among diverse video generation, editing, and intelligent reasoning tasks, integrating them into a holistic system. Unlike disjointed pipeline approaches, Kling-Omni supports a diverse range of user inputs, including text instructions, reference images, and video contexts, processing them into a unified multimodal representation to deliver cinematic-quality and highly-intelligent video content creation. To support these capabilities, we constructed a comprehensive data system that serves as the foundation for multimodal video creation. The framework is further empowered by efficient large-scale pre-training strategies and infrastructure optimizations for inference. Comprehensive evaluations reveal that Kling-Omni demonstrates exceptional capabilities in in-context generation, reasoning-based editing, and multimodal instruction following. Moving beyond a content creation tool, we believe Kling-Omni is a pivotal advancement toward multimodal world simulators capable of perceiving, reasoning, generating and interacting with the dynamic and complex worlds.