# How to Run Ollama on Windows (Install, GPU, Models)

> Install Ollama on Windows 10 22H2+, run your first model with ollama run, check it landed on the GPU, and move the model store off your C: drive.

- Canonical: https://guides-ai.pages.dev/guides/run-local-llm-ollama-windows/
- Plate 09.01 · Topic: Local LLMs (https://guides-ai.pages.dev/topics/local-llm/)
- Published: 10 Jun 2026 · Updated: 06 Sept 2026 · 3 min read
- Source site: guides-ai — https://guides-ai.pages.dev/

Ollama runs on Windows natively: download `OllamaSetup.exe`, run it, then `ollama run <model>`.
No administrator rights, no WSL, nothing leaves the machine.

## 1. Check what Windows needs

The floors come from Ollama's [Windows documentation](https://docs.ollama.com/windows):

| Requirement | What the docs state |
| --- | --- |
| Windows | 10 22H2 or newer, Home or Pro |
| NVIDIA driver | 551.61 or newer |
| AMD | a ROCm v7 / HIP7-capable or Vulkan-capable driver stack |
| Free disk | at least 4 GB for the binaries, plus room for models |

## 2. Install Ollama

```powershell
irm https://ollama.com/install.ps1 | iex
```

What it does: the one-liner from the download page; `OllamaSetup.exe` is the same install with a
wizard. It lands in your home directory, so no elevation prompt.

Short on space on C:? The installer takes a directory:

```powershell
.\OllamaSetup.exe /DIR="D:\ollama"
```

What it does: puts the binaries where you point it.

## 3. Pull and run your first model

```powershell
ollama run gemma4
```

What it does: downloads the model on first use — several GB — then opens a chat; `/bye` exits.
Any library tag works in its place; check its size against
[what fits in your RAM or VRAM](/guides/local-llm-ram-vram-requirements/) and
[the quantization you pick](/guides/choose-llm-quantization/).

## 4. Verify it worked

```powershell
ollama ps
```

What it does: lists the models loaded right now, with the memory each holds. Run it while a reply
is still streaming — an idle Ollama has nothing loaded.

```powershell
curl.exe http://localhost:11434/api/tags
```

What it does: asks the local server for its models. JSON back means [Ollama](/glossary/#ollama)
serves on port 11434 and your code can [call that API](/guides/call-ollama-api/). Use `curl.exe`,
not `curl` — PowerShell aliases the bare name to `Invoke-WebRequest`. Git Bash has the real one.

## 5. Move the model store off C:

Models land in `%HOMEPATH%\.ollama` and grow fast. The docs move the store with the
`OLLAMA_MODELS` variable, set through Windows Settings — the same User variable from a terminal:

```powershell
[Environment]::SetEnvironmentVariable('OLLAMA_MODELS', 'D:\ollama-models', 'User')
```

What it does: points the store at another drive. Quit Ollama from the tray and start it again; the
server reads the variable at startup.

## Failure mode: it answers, but at one word a second

That is the CPU doing the work. Two causes worth checking: a graphics driver below the floors
above, and a model bigger than your VRAM. Update the driver first; if nothing changes, drop to a
smaller tag or a lower
[quantization](/glossary/#quantization).

Ollama's Windows page documents the native build only. The Linux build inside WSL 2 is a separate
install with its own model directory.