Running a local model means your prompts and files can stay on your machine, you can work offline, and you’re not paying per token to test ideas. It’s also the fastest way to experiment with automation—because you can call a local model from scripts and workflows without waiting on a cloud API.
Ollama is one of the simplest “download → run a model” tools, and on Windows it runs as a native app and exposes a local API by default. 1
Table of Contents
Step 0 — Check requirements (so you don’t waste an hour)
Before you install anything, check these basics.
Windows version
Ollama’s Windows docs list Windows 10 22H2 or newer (Home or Pro) as the requirement. Windows 11 is fine. 1
GPU drivers (optional, but strongly recommended)
Ollama supports GPU acceleration on Windows, but your drivers need to be current. The Windows docs specifically call out minimum NVIDIA driver versions and that AMD users should install Radeon drivers. 1
Disk space
Local models are big. Even if you start with a smaller model, plan for multiple gigabytes. Ollama’s installer needs space too. 1
Step 1 — Install Ollama on Windows 11 (the clean way)
Install method: official Windows installer
Ollama’s docs say the easiest path on Windows is the OllamaSetup.exe installer. It runs as a native Windows application and makes the ollama command available in cmd/PowerShell/Terminal. 1
What to expect after install:
- Ollama runs in the background
- The command line tool works in PowerShell
- The local API is available automatically (we’ll test it later)
Step 2 — Verify Ollama is working
Open PowerShell and run:
PowerShellollama --help
If you see commands and usage output, you’re installed correctly.
Confirm the local API is available
Ollama’s API base is served (by default) at:
texthttp://localhost:11434/api
That base URL is documented in the Ollama API reference. 12
Step 3 — Download and run your first local model
The simplest onboarding move is: pick a small instruct model (so it answers like ChatGPT) and run it.
In PowerShell:
PowerShellollama run gemma3
Why I like starting this way:
- It’s a quick “does it work?” test
- It avoids huge downloads while you’re still setting up
Ollama’s API docs use gemma3 in example requests, so it’s a safe “known working” model name in their documentation. 12
If it’s slow
That’s normal on CPU. If you don’t have a dedicated GPU (or you’re on a laptop that’s not using the dGPU), responses may be slow. Some Windows setups default to CPU depending on GPU availability and driver situation (you’ll see this especially on integrated graphics laptops). 13
Step 4 — (Optional but recommended) Use a UI: Install Open WebUI on Windows
A lot of people love Ollama, but still want a browser UI (chat history, nicer prompt experience, multi-chat, etc.). That’s where Open WebUI shines.
Open WebUI’s docs include Windows commands and recommend setting DATA_DIR to avoid data loss. 3
Install Open WebUI
- Install Python (if you don’t have it)
- In PowerShell:
PowerShellpip install open-webui
Open WebUI docs show this as the pip install step. 3
Run Open WebUI (Windows)
Open WebUI docs show a Windows example using DATA_DIR and then starting the server. 3
Example:
PowerShell$env:DATA_DIR="C:\open-webui\data"
open-webui serve
Then open:
texthttp://localhost:8080
Open WebUI docs state the default access is at localhost:8080. 3
Connect Open WebUI to Ollama
Ollama runs its API locally at port 11434, and Open WebUI typically detects it or can be pointed at it.
If Open WebUI asks for the Ollama endpoint, use:
texthttp://localhost:11434
(That port is consistent with Ollama’s docs and examples.) 12
Step 5 — Use Ollama like a local “ChatGPT API” (localhost:11434)
This is where your blog can win SEO: lots of people want “local LLM + API” so they can connect it to apps, scripts, and automations.
The two endpoints you’ll use most
- Generate (single prompt → output)
- Chat (messages array → assistant response)
Ollama documents the base API URL and includes examples for both styles. 12
Example: call the chat endpoint with curl
Bashcurl http://localhost:11434/api/chat -d '{
"model": "gemma3",
"messages": [
{ "role": "user", "content": "Write a 3-step checklist for cleaning up a WordPress site." }
]
}'
This mirrors the structure shown in Ollama’s /api/chat documentation. 14
Why this matters for automation
Once you can reliably hit a local endpoint, you can:
- summarize customer emails locally
- classify content
- draft blog intros
- create structured JSON outputs for downstream tools
And you do it without sending prompts to a third-party API.
Step 6 — Troubleshooting (the stuff people search for)
“Ollama command not found” on Windows
This usually means the terminal session doesn’t see the executable yet. Close and reopen Terminal/PowerShell, or reboot if needed.
“Why is Ollama using CPU instead of GPU?”
Common causes:
- drivers not updated
- Windows is using integrated graphics for the process
- your model is too big for VRAM and spills to RAM/CPU
Ollama’s Windows docs emphasize GPU driver requirements and the Windows-native install behavior. 1
If you’re on a laptop/mini PC without a strong dGPU, you might consider LM Studio because it supports different acceleration paths and also offers a UI (this is a frequent recommendation in Windows-focused coverage). 13
“Open WebUI won’t start” (Windows)
The Open WebUI docs recommend Python environment managers and call out Python version expectations (3.11 is their dev environment). 3
“What if I want an OpenAI-compatible local server?”
If your goal is “reuse my OpenAI client code but run locally,” LM Studio supports OpenAI-compatible endpoints like /v1/chat/completions and documents how to change the base_url to localhost. 4
This is useful if you already have code written against OpenAI’s SDK.
FAQ (long-tail SEO)
Can I run a local LLM on Windows 11 without WSL?
Yes. Ollama runs as a native Windows application and provides the CLI and local API on Windows. 1
What port does Ollama use on Windows?
Ollama serves its API by default at localhost:11434. 12
What’s the easiest UI for Ollama on Windows?
Open WebUI provides a local web UI you can run yourself, and their docs show Windows setup steps and that it can be accessed on localhost:8080. 3
Conclusion + CTA
If you want the fastest “local LLM on Windows 11” setup, the winning combo is:
- Ollama for the local runtime + API
- Open WebUI for a clean chat UI
- (Optional) LM Studio if you want OpenAI-compatible endpoints and a polished desktop UI
