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 2.0 is comparable to global leading video generation models including the open-source HunyuanVideo and the closed-source Runway Gen-3 Alpha. By making Open-Sora 2.0 fully open-source, we aim to democratize access to advanced video generation technology, fostering broader innovation and creativity in content creation. All resources are publicly available at: https://github.com/hpcaitech/Open-Sora.

本文研究了AI视频生成模型的训练成本和效率，填补了高性能模型训练成本控制的空白。通过介绍Open-Sora 2.0模型的高效数据策划、模型架构、训练策略和系统优化等创新方法，本研究显示其在成本仅为20万美元的情况下，性能可与全球顶尖视频生成模型相媲美。这一开源模型有望促进视频生成技术的普及，激发更多创作和创新。

Open-Sora 2.0：以20万美元训练商业级视频生成模型