Hao AI Lab open-sources FastH3 Omni: MiniMax H3 distilled to 8 steps for reference-guided video and audio, with 5.6-11.9x lower end-to-end latency
On Oct 20, the FastVideo team at UCSD's Hao AI Lab open-sourced FastH3 Omni, a distilled version of MiniMax H3's reference-to-video-and-audio (Ref2VA) model that generates video with synchronized stereo audio from text plus up to nine images, video clips and voice references. Sampling drops from 50 steps to eight transformer evaluations, cutting end-to-end latency 5.6-11.9x on eight GB200s by the team's measurements. Training code is open, with NVFP4 weights for DGX Spark and RTX 5090 and ComfyUI support.
Key Takeaways
- Steps: eight transformer evaluations versus 50 for base MiniMax H3, via PDD plus DMD distillation
- Speed (team figures): 5.6-11.9x lower end-to-end latency across 27 matched workloads on 8x GB200; a 15-second single-image request drops from 139.69s to 14.14s
- Inputs: up to nine images, three videos and three audio clips, at most 12 references; output is 24 FPS video with 32 kHz stereo audio
- Local: NVFP4 QAD weights for DGX Spark (128 GB) and RTX 5090 (32 GB), 480p by default; FP8 weights for RTX 4090
- License: MiniMax-H3 Community License, not Apache or MIT
Linked Models & Agents:
