Sparse-vDiT replaces dense attention with fixed per-head sparse patterns chosen offline, achieving 1.58-1.85x end-to-end speedups on CogVideoX1.5, HunyuanVideo, and Wan2.1 with minimal quality loss.
Structural pruning for diffusion models
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Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers
Sparse-vDiT replaces dense attention with fixed per-head sparse patterns chosen offline, achieving 1.58-1.85x end-to-end speedups on CogVideoX1.5, HunyuanVideo, and Wan2.1 with minimal quality loss.