Model reference · open weights
FastVideo-FastH3-8-Step-Consumer is an open-weight video model from FastVideo. FastVideo-FastH3-8-Step-V2-NVFP4-Consumer (NVFP4) weighs 63.1 GB; the smallest configuration that runs it is L40S 48 GB.
For self-hosting, compare this build's requirements below with the GPU you plan to rent.
Summary of the FastVideo/FastVideo-FastH3-8-Step-V2-NVFP4-Consumer model card, 2026-10-06
What it is
| Released by | FastVideo |
|---|---|
| Released | 2026-10-05 |
| Parameters | 13.9B |
| VRAM | 63.1 GB for the weights |
What it runs on
| Card | Weights | Memory |
|---|---|---|
| RTX 3060 12 GB … RTX 5090 32 GB | does not fit | |
| L40S 48 GB | tight (encoders offloaded) | 44.0 GB |
| A100 80 GB | fits | 78.2 GB |
| H100 80 GB | fits | 78.1 GB |
| RTX PRO 6000 Blackwell 96 GB | fits | 93.8 GB |
| DGX Spark (GB10) 128 GB unified | fits | 107 GB |
| H200 141 GB | fits | 138 GB |
| B200 180 GB | fits | 176 GB |
From the model card
FastH3 V2 (8 distilled steps, video with synchronized audio) packaged for a single Blackwell GPU (RTX 5090, RTX PRO 6000) or a DGX Spark.
fastvideo_inference.json holds the 8-step DMD schedule, which FastVideo reads automatically.The 50 AdaLN timestep projections are 26 GB in BF16. transformer/adaln_tables.pt (155 MB) holds their precomputed
outputs for the 8-step schedule, so FastVideo can skip loading them:
import os
from huggingface_hub import hf_hub_download
os.environ["FASTVIDEO_H3_ADALN_TABLE"] = hf_hub_download(
"FastVideo/FastVideo-FastH3-8-Step-V2-NVFP4-Consumer", "transformer/adaln_tables.pt")
The table covers only the shipped schedule (fastvideo_inference.json); FastVideo raises an error for other timesteps.
For multi-GPU data-center serving, use FastVideo/FastVideo-FastH3-8-Step-V2-NVFP4. Smaller, faster experimental variant: FastVideo/FastVideo-FastH3-Trim-8-Step-NVFP4.
Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.