OPEN MODELS / AI video generation
Run FastH3-QAD-v2 on a cloud GPU
FastH3-QAD-v2 is a AI video generation model by FastVideo. See how much GPU memory it needs, which GPUs it fits on today and what it costs to run it yourself, billed per second.
GPUs it fits on today
Our estimate is about 35 GB for inference with BF16 weights, including working memory. Real use depends on resolution, batch size and context length.
| GPU | Memory | Per hour | 10 hours | |
|---|---|---|---|---|
| Q RTX 8000 | 45 GB | $0.48 | $4.80 | Rent |
| CMP 170HX | 64 GB | $0.62 | $6.20 | Rent |
| A100 SXM4 | 80 GB | $0.72 | $7.20 | Rent |
| RTX A6000 | 48 GB | $0.72 | $7.20 | Rent |
| A100 PCIE | 40 GB | $0.74 | $7.40 | Rent |
Live starting prices from our catalog. You pay per second while the machine runs.
How to run FastH3-QAD-v2
- 01
Rent a GPU
Pick one of the GPUs above. Billing is per second; stop the machine and you stop paying.
- 02
Open a terminal or Jupyter
Connect over SSH or open Jupyter in your browser. PyTorch and CUDA are ready to use.
- 03
Download and run the model
Run the commands below. The weights download straight from Hugging Face to your machine.
pip install -U diffusers transformers accelerate
huggingface-cli download FastVideo/FastH3-QAD-v2 --local-dir ./model
python -c "import torch; from diffusers import DiffusionPipeline; p = DiffusionPipeline.from_pretrained('./model', torch_dtype=torch.bfloat16).to('cuda'); print(p)"Why run it yourself?
Hosted video tools charge per clip or per month and put you in a queue. On your own GPU you pay only for the time it runs, make as many clips as you like and keep your prompts and files on your machine.
Questions
- How much GPU memory does FastH3-QAD-v2 need?
- By our estimate about 35 GB for inference (14B parameters). Higher resolution, longer context or bigger batches need more.
- How much does it cost to run FastH3-QAD-v2?
- From $0.48 per hour on Q RTX 8000, billed per second. Ten hours cost about $4.80.
- Do I need a subscription?
- No. You pay only for the time your machine runs, from your USD balance. Stop it whenever you are done.
Try it on your own GPU in minutes
Pick a GPU, open Jupyter or SSH and run any open model. You pay per second and can stop anytime; no subscription, no setup fee.
- Per-second billing in USD
- PyTorch and CUDA ready in minutes
- Rent from ChatGPT or Claude too