  We present AnimateDiff-Lightning for lightning-fast video generation. Our
model uses progressive adversarial diffusion distillation to achieve new
state-of-the-art in few-step video generation. We discuss our modifications to
adapt it for the video modality. Furthermore, we propose to simultaneously
distill the probability flow of multiple base diffusion models, resulting in a
single distilled motion module with broader style compatibility. We are pleased
to release our distilled AnimateDiff-Lightning model for the community's use.
