HunyuanVideo 1.5 Technical Report
Authors: name: Bing Wu; name: Chang Zou; name: Changlin Li; name: Duojun Huang; name: Fang Yang; name: Hao Tan; name: Jack Peng; name: Jianbing Wu; name: Jiangfeng Xiong; name: Jie Jiang; name: Linus; name: Patrol; name: Peizhen Zhang; name: Peng Chen; name: Penghao Zhao; name: Qi Tian; name: Songtao Liu; name: Weijie Kong; name: Weiyan Wang; name: Xiao He; name: Xin Li; name: Xinchi Deng; name: Xuefei Zhe; name: Yang Li; name: Yanxin Long; name: Yuanbo Peng; name: Yue Wu; name: Yuhong Liu; name: Zhenyu Wang; name: Zuozhuo Dai; name: Bo Peng; name: Coopers Li; name: Gu Gong; name: Guojian Xiao; name: Jiahe Tian; name: Jiaxin Lin; name: Jie Liu; name: Jihong Zhang; name: Jiesong Lian; name: Kaihang Pan; name: Lei Wang; name: Lin Niu; name: Mingtao Chen; name: Mingyang Chen; name: Mingzhe Zheng; name: Miles Yang; name: Qiangqiang Hu; name: Qi Yang; name: Qiuyong Xiao; name: Runzhou Wu; name: Ryan Xu; name: Rui Yuan; name: Shanshan Sang; name: Shisheng Huang; name: Siruis Gong; name: Shuo Huang; name: Weiting Guo; name: Xiang Yuan; name: Xiaojia Chen; name: Xiawei Hu; name: Wenzhi Sun; name: Xiele Wu; name: Xianshun Ren; name: Xiaoyan Yuan; name: Xiaoyue Mi; name: Yepeng Zhang; name: Yifu Sun; name: Yiting Lu; name: Yitong Li; name: You Huang; name: Yu Tang; name: Yixuan Li; name: Yuhang Deng; name: Yuan Zhou; name: Zhichao Hu; name: Zhiguang Liu; name: Zhihe Yang; name: Zilin Yang; name: Zhenzhi Lu; name: Zixiang Zhou; name: Zhao Zhong
Published: 2025-11-24 08:22:07

Abstract: We present HunyuanVideo 1.5, a lightweight yet powerful open-source video generation model that achieves state-of-the-art visual quality and motion coherence with only 8.3 billion parameters, enabling efficient inference on consumer-grade GPUs. This achievement is built upon several key components, including meticulous data curation, an advanced DiT architecture featuring selective and sliding tile attention (SSTA), enhanced bilingual understanding through glyph-aware text encoding, progressive pre-training and post-training, and an efficient video super-resolution network. Leveraging these designs, we developed a unified framework capable of high-quality text-to-video and image-to-video generation across multiple durations and resolutions.Extensive experiments demonstrate that this compact and proficient model establishes a new state-of-the-art among open-source video generation models. By releasing the code and model weights, we provide the community with a high-performance foundation that lowers the barrier to video creation and research, making advanced video generation accessible to a broader audience. All open-source assets are publicly available at https://github.com/Tencent-Hunyuan/HunyuanVideo-1.5.