FastVideo and Helios
These are competitors offering different optimization approaches for video generation—FastVideo prioritizes inference acceleration and post-training efficiency across unified frameworks, while Helios targets real-time long-form video synthesis as a specialized generative model, requiring users to choose based on whether they prioritize speed/flexibility or native long-video capability.
About FastVideo
hao-ai-lab/FastVideo
A unified inference and post-training framework for accelerated video generation.
Supports full model fine-tuning and LoRA adaptation for video diffusion transformers, alongside Distribution Matching Distillation and sparse attention techniques achieving >50x denoising speedup. Provides optimized inference through sequence parallelism and multiple attention backends (including Video Sparse Attention), with a Python API and CLI supporting H100/A100/4090 GPUs across Linux/Windows/macOS. Integrates with Hugging Face model hub and supports both autoregressive and bidirectional video generation architectures.
About Helios
PKU-YuanGroup/Helios
Helios: Real Real-Time Long Video Generation Model
Generates minute-scale video without anti-drifting strategies or standard acceleration techniques, achieving 19.5 FPS on single H100 GPU through novel architectural optimizations. Integrates with Diffusers, SGLang-Diffusion, vLLM-Omni, and Ascend-NPU, with support for group offloading and context parallelism across multiple GPUs while maintaining low VRAM footprint (~6GB).
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