OPEN MODELS / AI video generation
Run LTX-2.5-uncensored-v1.1-FP8 on a cloud GPU
LTX-2.5-uncensored-v1.1-FP8 is a AI video generation model by Artemio567. 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 17 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 2080 Ti | 22 GB | $0.25 | $2.50 | Rent |
| RTX 4000Ada | 20 GB | $0.39 | $3.90 | Rent |
| RTX 3090 | 24 GB | $0.41 | $4.10 | Rent |
| RTX 3090 Ti | 24 GB | $0.45 | $4.50 | Rent |
| Titan RTX | 24 GB | $0.45 | $4.50 | Rent |
Live starting prices from our catalog. You pay per second while the machine runs.
How to run LTX-2.5-uncensored-v1.1-FP8
- 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 Artemio567/LTX-2.5-uncensored-v1.1-FP8 --local-dir ./model --include "*Q4_K_M*"
# llama.cpp: ./llama-server -m ./model/*.gguf --host 0.0.0.0 --port 8000Why 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 LTX-2.5-uncensored-v1.1-FP8 need?
- By our estimate about 17 GB for inference (21B parameters). Higher resolution, longer context or bigger batches need more.
- How much does it cost to run LTX-2.5-uncensored-v1.1-FP8?
- From $0.25 per hour on RTX 2080 Ti, billed per second. Ten hours cost about $2.50.
- 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