[2503.09642] Open-Sora 2.0: Training a Commercial-Level Video Generation Model in $200k

Computer Science > Graphics arXiv:2503.09642 (cs) [Submitted on 12 Mar 2025 (v1), last revised 2 Mar 2026 (this version, v3)] Title:Open-Sora 2.0: Training a Commercial-Level Video Generation Model in $200k Authors:Zangwei Zheng, Xiangyu Peng, Yuxuan Lou, Chenhui Shen, Tom Young, Xinying Guo, Binluo Wang, Hang Xu, Hongxin Liu, Mingyan Jiang, Wenjun Li, Yuhui Wang, Anbang Ye, Gang Ren, Qianran Ma, Wanying Liang, Xiang Lian, Xiwen Wu, Yuting Zhong, Zhuangyan Li, Chaoyu Gong, Guojun Lei, Leijun Cheng, Limin Zhang, Minghao Li, Ruijie Zhang, Silan Hu, Shijie Huang, Xiaokang Wang, Yuanheng Zhao, Yuqi Wang, Ziang Wei, Yang You View a PDF of the paper titled Open-Sora 2.0: Training a Commercial-Level Video Generation Model in $200k, by Zangwei Zheng and 32 other authors View PDF HTML (experimental) Abstract:Video generation models have achieved remarkable progress in the past year. The quality of AI video continues to improve, but at the cost of larger model size, increased data quantity, and greater demand for training compute. In this report, we present Open-Sora 2.0, a commercial-level video generation model trained for only $200k. With this model, we demonstrate that the cost of training a top-performing video generation model is highly controllable. We detail all techniques that contribute to this efficiency breakthrough, including data curation, model architecture, training strategy, and system optimization. According to human evaluation results and VBench scores, Open-Sora ...