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

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.