Run LLaMA, Mistral, Gemma, and Qwen on your own hardware - no API key, no per-token bill.
Ollama packages open-weight language models - Llama 3, Mistral, Gemma, Qwen, DeepSeek, and dozens more - behind a simple local API, so a laptop-friendly model runs the same way whether you're calling it from a script, a chat UI, or an agent framework.
It's the piece almost every self-hosted AI stack sits on top of: Open WebUI, LibreChat, Flowise, and Langflow all talk to Ollama the same way they'd talk to OpenAI's API, just pointed at your own server instead.
Running it yourself means the prompts, the documents, and the conversation history never leave your infrastructure - and there's no usage meter running while you experiment.
| Image | ollama/ollama |
| Port | 11434 |
| Persistent volume | /root/.ollama |
Smaller models (7B-8B parameters, quantized) run acceptably on a 4-8GB RAM VPS with CPU-only inference - slow but usable for personal use. For real speed you want a GPU-backed server; DeployOS doesn't require one, but Ollama will use it automatically if the host has an NVIDIA GPU and the right drivers.
No - Ollama alone gives you an API you can call directly. Open WebUI just adds a ChatGPT-style browser interface on top, which is what most people actually want day to day.
Not quite the same models or polish, but functionally similar for a lot of use cases: your own chat interface, talking to a model that runs entirely on hardware you control, for the cost of the VPS instead of a monthly subscription.
Free download, no account needed. AI templates are on paid plans.
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