Run Wan2.1_T2V_14B_LightX2V_StepCfgDistill_VACE-GGUF on a cloud GPU
Wan2.1_T2V_14B_LightX2V_StepCfgDistill_VACE-GGUF is a Image to video model by QuantStack. 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 14 GB for inference with GGUF weights, including working memory. Real use depends on resolution, batch size and context length.
| GPU | Memory | Per hour | 10 hours | |
|---|---|---|---|---|
| RTX A4000 | 16 GB | $0.19 | $1.90 | Rent |
| RTX 2080 Ti | 22 GB | $0.20 | $2.00 | Rent |
| RTX 5060 Ti | 16 GB | $0.20 | $2.00 | Rent |
| Tesla V100 | 16 GB | $0.22 | $2.20 | Rent |
| Q RTX 5000 | 16 GB | $0.24 | $2.40 | Rent |
Live starting prices from our catalog. You pay per second while the machine runs.
How to run Wan2.1_T2V_14B_LightX2V_StepCfgDistill_VACE-GGUF
- 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 "huggingface_hub[cli]"
huggingface-cli download QuantStack/Wan2.1_T2V_14B_LightX2V_StepCfgDistill_VACE-GGUF --local-dir ./model --include "*Q4_K_M*"
# llama.cpp: ./llama-server -m ./model/*.gguf --host 0.0.0.0 --port 8000Why run it yourself?
Animating images on hosted services burns credits fast. A rented GPU has no credit limit: you pay per second and can try as many variations as you need.
Questions
- How much GPU memory does Wan2.1_T2V_14B_LightX2V_StepCfgDistill_VACE-GGUF need?
- By our estimate about 14 GB for inference (17B parameters). Higher resolution, longer context or bigger batches need more.
- How much does it cost to run Wan2.1_T2V_14B_LightX2V_StepCfgDistill_VACE-GGUF?
- From $0.19 per hour on RTX A4000, billed per second. Ten hours cost about $1.90.
- 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