What problem it solves

Developers need a straightforward way to run and manage open models while preserving control over where model interactions occur. The project provides local and cloud access, command-line workflows, a REST API, and client libraries for integrating models into existing applications.

Key features

• Run models from the command line — Start the model experience directly from the CLI, run a named model, or launch supported coding and assistant integrations.

  Source: README, cmd

• Use a REST API and client libraries — Run and manage models through the REST API, with Python and JavaScript libraries available for application development.

  Source: README

• Connect models to existing tools — Launch coding integrations, connect the platform to agents and applications, and use OpenClaw as a personal assistant across messaging services.

  Source: README, integration

• Deploy across supported platforms — Install for macOS, Windows, and Linux, or use the official Docker image for container-based deployment.

  Source: README, Dockerfile

Quick start

Copied verbatim from the project's README.

curl -fsSL https://ollama.com/install.sh | sh

ollama run gemma4

curl http://localhost:11434/api/chat -d '{
  "model": "gemma4",
  "messages": [{
    "role": "user",
    "content": "Why is the sky blue?"
  }],
  "stream": false
}'

Who it may suit

Inference: may suit developers who want to run open models locally, connect them to coding tools and agents, or build model-enabled applications through an API or language-specific library.

Topics to discuss

• Which local and cloud workflows should be expanded in the next release?

• How should model integrations be improved for coding agents and messaging assistants?

• What documentation would help developers build, deploy, and manage their first model application?

Written by ReadmeX AI from the project's README, source and public GitHub data; it may contain mistakes.

Read the original README https://github.com/ollama/ollama#readme

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