What it does
Ollama is a local model runner with a command-line interface, desktop application, and documented REST API. Developers can download a model, run it on their own machine, and connect scripts, libraries, or coding tools to the local service. Ollama also offers hosted model access, so users can choose local inference or use its cloud plans. The local software is MIT-licensed; that software license should not be confused with the terms for a specific model or with the account-based cloud offering.
Start with a local model
Install the app for macOS, Windows, or Linux and choose a local model. The official repository gives ollama run gemma4 as a starting command. Ollama downloads or selects the model and provides a chat workflow through its app or terminal. For a small application, use the local REST endpoint or an official Python or JavaScript library to send prompts to the running service. This can make a useful first task a private codebase explainer: ask a local model to summarize a directory's structure, then decide whether the answer is sufficient before connecting it to an editor or agent. Local use does not require signing in; the quick start asks users to sign in for cloud models or choose a local model. The pricing page shows a free option for local use and hosted usage, alongside paid cloud plans. The model runs on the user's own machine, so capacity and response quality depend on the selected model and available hardware. The Ollama MIT license applies to the software, not automatically to model weights. Check the selected model's own license and usage terms before distributing or embedding it.
Strengths
- Runs supported models locally without requiring an Ollama cloud account.
- Provides a local REST API plus official Python and JavaScript libraries.
- Connects to a range of coding tools and desktop applications through documented integrations.
Watch out for
- Local model execution uses the developer's own machine resources, and performance varies by model and hardware.
- Cloud models require an account and have separate usage terms from the local runner.
Best for
- Trying local language models from a terminal or desktop application.
- Prototyping model-backed developer tools against a local REST endpoint.
Sources
- Ollama · Run AI models locally and in the cloud (Oct 25, 2026)
- Quickstart - Ollama (Oct 25, 2026)
- ollama/ollama (Oct 25, 2026)
- Ollama Pricing (Oct 25, 2026)
- MIT License (Oct 25, 2026)