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.
VRAM needed by model
Approximate memory for the model weights. Actual use grows with batch size, context length and framework.
| Model | VRAM needed | Starter (12 GB) | Standard (24 GB) | Pro (24 GB) | Power (48 GB) |
|---|---|---|---|---|---|
| Stable Diffusion XL (inference) | 8–12 GB | Yes | Yes | Yes | Yes |
| Llama 3 8B (4-bit) | ~6 GB | Yes | Yes | Yes | Yes |
| Llama 3 8B (16-bit) | ~16 GB | No | Yes | Yes | Yes |
| Mixtral 8x7B (4-bit) | ~26 GB | No | No | No | Yes |
| Llama 3 70B (4-bit) | ~40 GB | No | No | No | Yes |
How you work on it
Pricing
Start at $0.40/hr on Starter, or take the 48 GB Power tier for larger models. Charged by the second, stop anytime.