Ollama

Ollama is a local LLM runtime that lets you download and run open models on your own computer, then use them through a command line, local server, or API.

Why people choose it

Ollama reduces the setup friction around local models. Its official model library covers coding, vision, embeddings, and reasoning models, while the runtime exposes a local API that applications can call without sending local requests to a hosted provider.

What is included

The project provides model download and management commands, a local server, REST endpoints, and official Python and JavaScript libraries. It also offers OpenAI-compatible and Anthropic-compatible endpoints, which makes it useful as a backend for Open WebUI, coding tools, and custom applications.

Deployment requirements

The workload is determined by the model, context size, quantization, and whether inference uses CPU or GPU acceleration. The official docs do not promise one universal RAM or VRAM minimum, so size the host for the specific models you intend to run. The local API normally listens at `http://localhost:11434`; protect it before binding it beyond the host.

Main tradeoffs

Ollama is a runtime, not a complete team chat product or model guarantee. Local inference trades provider dependence for hardware, storage, download time, and update responsibilities. Model licenses and capabilities vary, so review each model before using it commercially or with sensitive data.

Best fit

Choose Ollama if you want a straightforward local model runtime for experimentation, private workloads, development, or as a backend for another interface. If you only need a hosted API, Ollama Cloud or another provider may require less hardware management.