Train and run models on a cloud GPU.

12 GB to 48 GB of VRAM. PyTorch and CUDA preinstalled, JupyterLab in your browser, SSH when you want it. Charged by the second while it runs.

What you can use

PyTorch comes preinstalled. Everything else is a pip install away — you are root in your Linux container.

PyTorch + CUDA

Preinstalled — the machine starts from the official PyTorch image

JupyterLab

Notebooks, a terminal and a file browser, opened from your dashboard

Hugging Face Transformers

pip install transformers to load and run open language models

Hugging Face Diffusers

pip install diffusers for image-generation models such as Stable Diffusion

Your training scripts

Upload your code and run it from a terminal or over SSH

Fine-tuning

Fine-tune models with your own data, e.g. LoRA with pip install peft

Any pip package

You are root in the container — install the libraries you need

Long-running jobs

Start jobs with nohup so they keep running after you disconnect

VRAM needed by model

Approximate memory for the model weights. Actual use grows with batch size, context length and framework.

ModelVRAM neededStarter (12 GB)Standard (24 GB)Pro (24 GB)Power (48 GB)
Stable Diffusion XL (inference)8–12 GBYesYesYesYes
Llama 3 8B (4-bit)~6 GBYesYesYesYes
Llama 3 8B (16-bit)~16 GBNoYesYesYes
Mixtral 8x7B (4-bit)~26 GBNoNoNoYes
Llama 3 70B (4-bit)~40 GBNoNoNoYes

How you work on it

JupyterLab in your browser

Click Open Studio on your machine's page. Notebooks, a terminal and a file browser for uploading data and downloading results — nothing to install on your computer.

PyTorch and CUDA ready

Run torch.cuda.is_available() in a notebook and it returns True. The CUDA compiler (nvcc) is not included; install the CUDA toolkit yourself if you need to build CUDA code.

SSH for scripts and long jobs

Add your public key from a Studio terminal, then connect as root with the SSH command on your machine's page. Charges run while the machine runs, so stop it when the job is done.

Pricing

Start at $0.40/hr on Starter, or take the 48 GB Power tier for larger models. Charged by the second, stop anytime.

Starter
GPURTX 3060
VRAM12 GB
$0.40/hr

Notebooks, smaller models and experiments

Standard
GPURTX 3090
VRAM24 GB
$0.60/hr

Larger models and bigger batches

Power
GPURTX A6000
VRAM48 GB
$1.20/hr

The most VRAM: 70B-class models at 4-bit

View all plans →

Run your first model — $0.60/hr