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Developer Frameworks & Infrastructure

Ollama

Run open models locally with one command

Open sourceRuns on your device

Pricing

Open Source

Free

Platforms

macOS - Windows - Linux

Self-hosted or local

Category

Developer Frameworks & Infrastructure

133 tools

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Last updated

Sep 30

Listing updated

Best for

Prototype LLM features offline

Pull a model with one command and test prompts, RAG flows, or agents locally with no API cost and no data leaving the laptop.

Pricing checked Sep 2026

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About Ollama

Ollama is an open-source tool that packages large language models such as Llama, Mistral, Gemma, Qwen, and DeepSeek into single-command downloads that run on your own machine. A model registry, automatic hardware detection, and a Modelfile format for customizing system prompts and parameters reduce what used to be a GPU configuration project to something like installing an app.

It exposes a local REST API plus an OpenAI-compatible endpoint, so code written for cloud chat services can be pointed at localhost instead. It runs on macOS, Linux, and Windows, accelerates well on Apple Silicon, and can serve multiple models on capable hardware. It suits developers prototyping without API bills, teams with privacy or offline constraints, and tinkerers quantizing models to fit consumer GPUs; production-scale serving still calls for dedicated infrastructure.

  • One-command install and model downloads across macOS, Linux, and Windows
  • OpenAI-compatible local API makes swapping cloud models for local ones trivial
  • Free and MIT licensed, with a simple Modelfile format for custom variants
  • Runs well on Apple Silicon laptops, not just servers
  • Quality and speed depend on your hardware; small models trail frontier cloud models
  • Interface is a CLI at heart; chat frontends come from third parties
  • Long contexts and large models need substantial RAM or VRAM
Terminal Install CommandLocal / CLI
$curl -fsSL https://ollama.com/install.sh | sh

Get up and running with large language models locally. Install via shell script or download native desktop binary.

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