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TurboDiffusion: Video Diffusion Model Acceleration Framework Achieves 100-200x Speedup

By

meander_water

5mo ago· 15 min readenCode

Summary

TurboDiffusion is a video generation acceleration framework that can speed up end-to-end diffusion generation by 100-200 times on a single RTX 5090 GPU while maintaining video quality. The framework uses SageAttention, SLA (Sparse-Linear Attention) for attention acceleration, and rCM for timestep distillation. The repository provides the official implementation, though checkpoints and paper are not yet finalized and will be updated later to improve quality.

Key quotes

· 4 pulled
TurboDiffusion, a video generation acceleration framework that can speed up end-to-end diffusion generation by $100 \sim 200\times$ on a single RTX 5090, while maintaining video quality.
TurboDiffusion primarily uses SageAttention, SLA (Sparse-Linear Attention) for attention acceleration, and rCM for timestep distillation.
Paper: TurboDiffusion: Accelerating Video Diffusion Models by 100-200 Times
Note: the checkpoints and paper are not finalized, and will be updated later to improve quality.
Snippet from the RSS feed
TurboDiffusion: 100–200× Acceleration for Video Diffusion Models - thu-ml/TurboDiffusion

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