Model Releases
FastVideo FastH3 V1: Open source 4-step Sparse Distilled H3 checkpoint/LORA
Hey guys, FastVideo team here. We saw how important speed and quality is for everyone. And we've been working to create our own step distill checkpoints and LORAs for MINIMAX h3. Here's is our v1 rele
Hey guys, FastVideo team here. We saw how important speed and quality is for everyone. And we've been working to create our own step distill checkpoints and LORAs for MINIMAX h3. Here's is our v1 release! Important links first: - FastVideo: https://github.com/hao-ai-lab/FastVideo - Blog (contains more examples and details): https://haoailab.com/blogs/fasth3-preview/ - Checkpoints and LoRAs: https://huggingface.co/FastVideo/FastVideo-FastH3-4-step-Preview-v1-LoRA Do note that the VSA checkpoint/LORA will require VSA kernel We also released a LORA with dense attention that should be easy to test for everyone. We are already working on improving both this T2AV checkpoint as well as getting a distill of Ref2VA out as well. We are taking great care to make sure the quality and audio is as best as possible. We realize not everyone have blackwell GPUs lying around and please stay tuned for our targeted optimizations for local AI hardware, including RTX GPUs, DGX Sparks, and Apple MLX. We release numbers on B200s just because this is our current compute platform for post-training. We want to be as open as possible with the community! Quality We used 1k+ B200 training hours, paired with real world multi-shot, visual audio synced input distribution and output formats for best possible quality preservation. FastH3 natively supports variable resolution, aspect ratio, and duration. In a single checkpoint. Openness Start with the 4-step VSA / Data-Free checkpoint, our recommended FastH3 Preview v1 release. We provide full weights and a pre-extracted LoRA, plus dense and synthetic-data ablations. Fully open source with training (coming soon!) and inference code recipe for your customization. What’s Next Follow us along for image ref (FL2VA) and full omni ref (Ref2VA) coming in the next a few weeks Motion and more generation quality improvements Nvfp4 and GPU memory reduction. Optimizations targeting local AI devices including RTX, DGX Sparks, and Apple MLX. New training runs using FastGen team’s new Parallel Decoding Distillation (PDD) method! If you find any issues or have questions please raise issues on our github! submitted by /u/Solitary_Thinker [link] [comments]
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Source: r/StableDiffusion | 2026-08-28