curl -fsSL https://ollama.com/install.sh | sh, then chat with a small model using ollama run llama3.2:3b. Ollama listens only on 127.0.0.1:11434. For a web chat, run Open WebUI in Docker with --network=host and reach it through an SSH tunnel or a reverse proxy. Without a GPU, answers are slow, so use small models.
Before you start
- Ollama downloads and runs open large language models (LLMs) on your own server. Open WebUI is a web chat interface for it.
- Expect CPU-only speed. On a VPS without a GPU, Ollama runs the model in system memory on the CPU. Replies arrive word by word, far slower than on a GPU, and long answers can take minutes. Larger models are slower still. This guide assumes a CPU-only server.
- Pick small models. The model must fit in free RAM with room for the operating system and the conversation (context). Use the table below.
- Install Docker if you want Open WebUI.
Which model should I use on a CPU-only VPS?
Sizes are from the Ollama library on 4 November 2026. Models of 7B parameters and more work only with plenty of RAM and patience.
How to install Ollama
1
Run the install script
ollama systemd service.2
Check it is running
3
Download and chat with a model
/bye to leave.How to check it worked
ollama ps lists the loaded model; 100% CPU in the PROCESSOR column means it runs fully in system memory. The curl call returns a JSON answer.
How to add Open WebUI
1
Create a secret key
2
Start Open WebUI
--network=host lets the container reach Ollama on 127.0.0.1, so Ollama never needs to listen publicly. Open WebUI then listens on port 8080 of the server.3
Open it through an SSH tunnel
On your own PC, run:Then open
http://localhost:8080 in your browser.4
Create the admin account
The first account you create becomes the administrator, and sign-up closes after it. Create it straight away.
How to manage Ollama
Models are stored in
/usr/share/ollama/.ollama/models. Check free space with df -h before pulling large models. To store them elsewhere, set OLLAMA_MODELS with sudo systemctl edit ollama and give the ollama user access to that folder.
Frequently asked questions
Can I run Ollama on a VPS without a GPU?
Yes. Ollama runs on the CPU and system memory when there’s no supported GPU. It works well for small models and light use, but it is much slower than a GPU.Why is Ollama so slow on my VPS?
Without a GPU, every word is computed on the CPU. Use a smaller model, keep questions short, and avoid running other heavy jobs at the same time. Check load with htop.How long does a model stay in memory?
5 minutes after the last request by default. SetOLLAMA_KEEP_ALIVE with sudo systemctl edit ollama to change it, or 0 to unload straight away.
Why does Ollama get killed or the server freeze?
The model plus context needed more RAM than was free, so Linux ended the process. Use a smaller model, add swap as a buffer, and see fix out-of-memory killed processes.Related guides
VPS and dedicated server guides
Every guide in this section.
Install Docker
Needed for Open WebUI.
Check memory usage
See if a model fits in RAM.
Nginx reverse proxy
Serve Open WebUI on your domain.
Benchmark your VPS
Measure CPU and memory speed.
Checked against the official Ollama Linux docs, Ollama FAQ and Open WebUI docs on 4 November 2026. Model names and sizes change as new models are released.
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Last Updated: November 2026