# RGPU – Use a remote Nvidia GPU from PyTorch on a machine that has none

> Source: <https://rgpu.dev>
> Published: 2026-09-23 03:27:01+00:00

rGPU / Product documentation

# Your code, here.

Your GPU, anywhere.

Keep Python on your laptop. Run PyTorch operations and hold tensors on a remote GPU, including from a Mac with no CUDA installation.

 Local code · remote GPU

Python stays with you. Tensors stay on the GPU.

 train.py · local Python

``` python
import rgpu, torch

x = torch.randn(1024, 1024, device="rgpu")
y = (x @ x).relu().sum()
print(y.item())
```

Local Python → SSH tunnel → GPU server

## Train with PyTorch

Move a model, run autograd, and ship compiled graphs.

## Use the CUDA shim

Keep device="cuda" with the Linux driver-remoting path.

## Understand the cost

Measure host waits, transfers, and completed GPU work.

Built for trusted GPU hosts. [Read the deployment guidance](https://rgpu.dev/docs/operations/) before connecting.