# How to install Ollama on Windows 11 (Ryzen AI mini PC)

How-to · Local AI · 2 min read. By [David Wilson](https://testbenchlab.com/authors/david-wilson/). Updated 2026-10-02.

Install Ollama, run a small model and check which processor is used. A successful response does not prove Radeon acceleration. Current documentation includes a Vulkan route for additional GPU support.

**Requirements:** Windows 11, current graphics drivers, storage and internet for initial downloads. This procedure follows upstream documentation; it is not a claimed execution test on a specific device.

## Install Ollama

Download the official Windows installer from ollama.com. After installation, open a new PowerShell window and run:

```powershell
ollama --version
ollama run qwen2.5:3b
```

The first run downloads model data. Complete the download before judging response speed.

## Make Ollama use the Radeon iGPU

Install the appropriate AMD graphics driver, restart Ollama and run a prompt. Current documentation says Vulkan is enabled by default when the backend is installed. Inspect `ollama ps` while the model is loaded. CPU-only use calls for a driver/backend check; the NPU is a separate path.

## Pick a model that fits your memory

Begin with the 3B example. Context and other applications increase memory use beyond downloaded weights. Close unnecessary workloads and reduce context before assuming a larger computer is the only answer to an allocation error.

## Add a chat UI (Open WebUI)

With uv installed, use the documented Windows route:

```powershell
$env:DATA_DIR="C:\open-webui\data"
uvx --python 3.11 open-webui@latest serve
```

Open the address printed by the process and connect to Ollama at `http://localhost:11434`. Keep access local unless you deliberately configure authenticated wider use.

## Frequently asked questions

### Does Ollama work on AMD GPUs?

Yes, through supported backends and drivers. Check current platform support and verify actual offload.

### How much RAM do I need for Ollama?

Small quantised models use modest memory, but leave room for Windows and context. 32GB is a useful starting point for broader experimentation.

## Related reading

- [How much RAM do you need to run a local LLM?](https://testbenchlab.com/guides/how-much-ram-for-local-llm/)
- [Run local LLMs on the Ryzen AI NPU with Lemonade Server](https://testbenchlab.com/guides/run-llms-on-ryzen-ai-npu-lemonade-server/)
- [llama.cpp with Vulkan on a Radeon iGPU](https://testbenchlab.com/guides/llama-cpp-vulkan-radeon-igpu/)
- [AI mini PCs](https://testbenchlab.com/categories/ai-mini-pcs/)

## Sources

1. [Ollama Windows documentation](https://docs.ollama.com/windows)
2. [Ollama hardware support](https://docs.ollama.com/gpu)
3. [Open WebUI quick start](https://docs.openwebui.com/getting-started/quick-start/)