Video generation is bottlenecked by latency, memory, and training cost as much as imagination. FastVideo focuses on making inference and post-training fast enough for iteration.
What Sets It Apart
It combines finetuning, LoRA, preprocessing, distillation, sparse attention, sequence parallelism, and multiple attention backends in one stack. Speed-oriented engineering around open video DiTs helps teams move from single-GPU demos to larger experiments.
Who Should Use It
Great fit if you research or deploy open video-generation models and need faster inference plus post-training control. Look elsewhere if you want a simple creative UI.