SANA-Video 2.0

NVIDIA Research's Efficient AI Team and Singapore Lab introduced SANA-Video 2.0, a hybrid video diffusion transformer at 5B and 14B scales that generates 720p video on a single H100 GPU. The model achieves a VBench score of 84.30 in 13.06 seconds for 720p/5s, is 3.2× faster than a full-softmax baseline at 720p/60s, and 120× faster than Wan 2.2 14B on one H100, using hybrid linear-softmax attention and block attention residuals to match full-softmax quality with linear attention efficiency.

NVIDIA Research · Efficient AI Team & Singapore Lab SANA-Video 2.0 Hybrid Linear Attention with Attention Residuals for Efficient Video Generation 84.30 VBench Total 13.06s 720p/5s · one H100 3.2× faster than softmax at 60 s 120× faster than Wan 2.2 14B One-H100 latency 720p / 5s · one H100 · 40 steps 120× 1556 788 130 69.3 13.06 log scaleseconds ↓ Paper overview Abstract Hybrid Linear Attention with Attention Residuals for Efficient Video Generation We introduce SANA-Video 2.0 , a hybrid video diffusion transformer instantiated at 5B and 14B scales under a unified architecture. Designed to generate high-quality video up to 720p on a single GPU, SANA-Video 2.0 matches full-softmax video DiTs in quality while retaining the favorable long-sequence scaling of linear attention. To avoid quadratic attention throughout, Hybrid Linear-Softmax Attention combines gated linear attention for O N -dominated mixing with periodic gated-softmax anchors at a 3:1 ratio, restoring the full-rank token interactions that pure linear attention lacks. To propagate these refreshed representations across depth, Block Attention Residuals AttnRes route completed block summaries into later linear layers, enabling anchor-feature reuse and boosting deep-layer effective rank by ~12%. Through from-scratch training, SANA-Video 2.0 learns the complete hybrid directly rather than linearizing pretrained models, with reduced-resolution proxy studies establishing 25% softmax as the optimal quality-efficiency trade-off. With 40-step sampling, SANA-Video 2.0 achieves a VBench score of 84.30 in 13.2s at 480p on a single H100, remaining competitive with far larger softmax video DiTs at a fraction of the latency. Its compiled DiT forward pass is 3.2× faster than a matched full-softmax baseline at 720p/60s, a gap that expands with video duration. Furthermore, full-stack Sol-Engine optimization kernel fusion, caching, and sparse attention accelerates this hardware-friendly backbone by a further 3.58× , bringing the 5B pipeline to 13.06s at 720p/5s and making it 120× faster than Wan 2.2-A14B on one H100. Overall, our hybrid design recovers softmax-level expressiveness at substantially reduced cost, unlocking scalable long, high resolution video generation.