AI BriefingFlexible Video Diffusion
·2026.07.10 09:00
Key point
Flex-Forcing flexibly switches how video diffusion models generate by chunking temporal and denoising steps.
Details
Flex-Forcing is a technique that trains video diffusion models to freely switch between bidirectional generation and autoregressive generation.
This approach flexibly adjusts the temporal range and denoising-step chunking, providing the following benefits.
- Improved Inference speed
- Enhanced Video quality
- Ensured Long-range stability across diverse compute environments
Through this, users can enjoy optimized video generation performance tailored to their available compute budget.
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