# Installing PyTorch with ROCm on Radeon GPUs

> Step-by-step guide to installing PyTorch with ROCm support on Ubuntu for AMD Radeon (RDNA2) GPUs – venv setup, pip install, and GPU verification.

*Source: https://velstech.net/install-pytorch-rocm-ubuntu · Updated: 2026-08-25 · Category: Tutorials · Tags: PyTorch, ROCm, Radeon*

*Markdown version of [Installing PyTorch with ROCm on Radeon GPUs](https://velstech.net/install-pytorch-rocm-ubuntu). [Read the full guide with interactive tools](https://velstech.net/install-pytorch-rocm-ubuntu).*
*Also as Markdown: [Hindi](https://velstech.net/install-pytorch-rocm-ubuntu.hi.md) · [Tamil](https://velstech.net/install-pytorch-rocm-ubuntu.ta.md).*

---

PyTorch is the go-to framework for deep learning, and on AMD hardware it runs
through **ROCm**. Once ROCm is installed, getting PyTorch working on
a Radeon GPU is just a `pip install` away.

I tested this on a **Radeon RX 6800M** (gfx1031, RDNA2) with ROCm
7.14 on Ubuntu 26.04 – the exact commands below are what worked. The same flow
applies to other RDNA2/RDNA3 cards; just swap the gfx target in the install
command.

## Prerequisites

- ROCm installed and verified – if you haven't done this yet, follow
our Installing ROCm on Ubuntu for Radeon GPUs
guide first, and confirm rocminfo shows your GPU.

- Python 3.11, 3.12, 3.13, or 3.14 installed.

- Your GPU's gfx architecture (e.g. gfx1031 for RX 6800M).

## Step 1 – Create a virtual environment

Always install PyTorch in a fresh virtual environment so it never conflicts with
system packages or other Python projects:

```
python3.12 -m venv .venv
```

Use whichever Python version you have – `python3.11`,
`python3.13`, or `python3.14` all work. This creates a
folder called `.venv` in your current directory.

## Step 2 – Activate the environment

Activate it so `python` and `pip` point at the venv:

```
source .venv/bin/activate
```

You'll know it worked when the prompt shows `(.venv)` at the start.

## Step 3 – Install PyTorch with ROCm support

Install the ROCm-enabled PyTorch, torchvision, and torchaudio from AMD's wheel
repository. Use your GPU's `device-gfx` target – for the RX 6800M that's
`device-gfx1031`:

```
python -m pip install --index-url https://repo.amd.com/rocm/whl-multi-arch/ \
    "torch[device-gfx1031]==2.12.0+rocm7.14.0" \
    "torchvision[device-gfx1031]==0.27.0+rocm7.14.0" \
    "torchaudio==2.11.0+rocm7.14.0"
```

A few notes:

- The [device-gfx1031] extra pulls in the ROCm libraries tuned for
your exact GPU architecture – don't skip it.

- For other cards, swap the target: gfx1030 (RX 6800/6700 XT), gfx1100 (RX 7900
XTX), and so on. Or use [device-all] if you want support for every
architecture at once (larger download).

- The +rocm7.14.0 version tag must match your installed ROCm release.

> If pip complains about resolving dependencies, make sure the venv is active and
> you're passing --index-url https://repo.amd.com/rocm/whl-multi-arch/ –
> that repository is what AMD publishes the ROCm builds to.

## Step 4 – Verify the GPU is detected

Run this one-liner to confirm PyTorch sees your AMD GPU:

```
python -c "import torch; print(torch.cuda.is_available())"
```

It prints `True` if PyTorch and ROCm are installed correctly and your
AMD GPU is detected. (Yes, it's `cuda` in the API – PyTorch keeps the
same interface for ROCm so code is portable.)

You can go further and check the device name:

```
python -c "import torch; print(torch.cuda.get_device_name(0))"
```

On the RX 6800M this reports something like `AMD Radeon RX 6800M`.

## What's next?

With PyTorch running on ROCm you can:

- Train models and run inference with full GPU acceleration

- Run LLMs locally – Hugging Face Transformers, text-generation-webui, and similar tools work out of the box

- Use torchvision for image models and torchaudio for audio pipelines

The official guide has more detail if you need it:
[Install PyTorch for ROCm – AMD AI ecosystem docs](https://rocm.docs.amd.com/projects/ai-ecosystem/en/latest/frameworks/pytorch/install.html).

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*VelsTech – technology explained for everyone. Original: https://velstech.net/install-pytorch-rocm-ubuntu*