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Ollama

Runs open AI models like Gemma, Qwen and DeepSeek on your own machine or in the cloud.

Stars
186k
Forks
18.9k
Licence
MIT
Language
Go
Last update
4 days ago
Type
App

What it is

Ollama is a tool for downloading and running open-weight AI language models locally, with a simple command line and a REST API. The README says it also offers cloud access and can connect to coding tools and assistants such as Claude Code, Codex and OpenClaw. People use it to try models privately or to build apps that call a model through a local API.

  • Run a model such as Gemma 4 from the terminal with a single command
  • Send chat requests to a local REST API at localhost:11434
  • Call models from Python or JavaScript using the official client libraries
  • Launch an integration with a coding tool such as Claude Code or OpenCode
  • Connect a community chat interface like Open WebUI to a local Ollama instance

Great for

  • Developers who want a local model API for their own apps
  • People who want to chat with open models without sending prompts to a hosted service
  • Users who want to connect a coding assistant to a local or self-chosen model
  • Students experimenting with different open models from a terminal

Not ideal for

  • People who need the most capable closed frontier models, since this focuses on open models
  • Users with limited disk space or memory, because model files can be large and need capable hardware (the README does not give specific requirements)
  • Non-technical users who want a polished desktop app with no terminal use, although the README mentions a download option for macOS and Windows
Step-by-step guide: how to use OllamaInstall, first run, examples, tips and FAQs

How to get it

  1. 1

    Install with a package manager

    macOS and Linux install

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

    Windows install (PowerShell)

    irm https://ollama.com/install.ps1 | iex

    Install Python client

    pip install ollama

    Install JavaScript client

    npm i ollama
  2. 2

    Run it

    • Install Ollama using the command for your operating system
    • Run `ollama` in a terminal to be prompted to run a model or connect an app
    • Run `ollama run gemma4` to chat with the Gemma 4 model
    • Or send a request to the REST API at http://localhost:11434/api/chat
  3. 3

    Get the most out of it

    • Use `ollama launch` with a supported integration such as Claude Code, Codex or OpenCode
    • Browse the model library at ollama.com/library for other models
    • Use the Python or JavaScript libraries to build your own apps on the local API
    • Try a community web or desktop interface such as Open WebUI or AnythingLLM
    • Read the Modelfile and API documentation to customize models

Downloads

Strengths

  • Simple install and run commands across macOS, Windows, Linux and Docker
  • Official Python and JavaScript libraries plus a documented REST API
  • Large community with many integrations listed in the README

Trade-offs

  • The README is truncated and does not state hardware requirements or model sizes
  • Some features, such as cloud access and specific integrations, depend on Ollama's own services and documentation that is only partly described here
  • Model quality and licensing depend on each individual model, not on Ollama itself

How it compares

ProjectStarsTypeLevelUpdatedBest for
ollama (this)186kAppbeginner4 days agoDevelopers who want a local model API for their own apps
llama.cpp133kLibraryintermediate4 days agoDevelopers who want to run open-weight models locally without a cloud API
mindshub39.8kAppintermediate13 days agoKnowledge workers who want to automate reading and writing tasks like reports and recurring workflows
OmniRoute83.8kAppintermediate4 days agoDevelopers who use several AI coding tools and want one place to configure providers
DeepSeek-Reasonix36kAppbeginner4 days agoDevelopers who want an AI assistant to make multi-step changes in a local project
magpie28.2kAppintermediate4 days agoPeople who use more than one AI coding agent and want one place to manage their models

Stats synced from GitHub. The assessment above was drafted with AI from the project's README on 2026-10-29 and may miss recent changes — check the README before relying on a command. MIT licence: free to use, modify and distribute, including commercially, as long as you keep the copyright notice.