Ollama

Open-source runtime for running large language models locally on Mac, Windows, and Linux.

Open Source Coding & Development
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What is Ollama?

Ollama is the standard open-source tool for running large language models on your own machine. One command downloads and runs models like Llama, Mistral, DeepSeek, Gemma, and Qwen with no cloud account, no per-token fees, and no data leaving the device. It handles model management, quantization, and GPU/CPU memory allocation under the hood, exposes a REST and OpenAI-compatible API for app integrations, and has become the default local backend that AI agents and developer tools target.

Key features

  • One-command local model download and execution
  • Large registry of open models (Llama, Mistral, Gemma, Qwen, DeepSeek)
  • Automatic quantization to fit consumer hardware
  • REST API and OpenAI-compatible endpoint on localhost
  • Cross-platform: macOS, Windows, Linux
  • GPU acceleration with CPU fallback

Watch: Ollama tutorial

Learn how to run AI LLM models locally on your own computer completely for FREE in under 10 minutes! Learn how to run AI LLM models locally on your own computer completely for FREE in under 10 minutes! — Luke Saunders (System Integration)

Video by Luke Saunders (System Integration) on YouTube — plays here without leaving this page.

Pros

  • Free, open-source, fully offline
  • Zero per-token cost and no data leaves the machine
  • Huge model library with simple versioning
  • De facto standard local backend for agents

Cons

  • Model quality depends on local hardware; large models need serious RAM/VRAM
  • No cloud sync or managed scaling
  • Less guardrailing than managed model APIs

Ollama at a glance

PricingOpen Source
CategoryCoding & Development
Platformswindows, macos, linux, api
CompanyOllama
Official websiteollama.com
local-llmopen-sourcellm-runtimeprivacyapimodel-inference

How to choose the right Coding & Development tool

The right coding tool depends on where you write code and how much of your codebase it can understand. IDE integration is the first filter — a tool that lives in your editor, sees your project files and respects your stack will help far more than a general chatbot you paste snippets into. Look for accurate completions, clear explanations of suggested changes, and strong refactoring and debugging support for your main languages. Privacy deserves real attention: check whether your code is used for training, and whether a self-hosted or enterprise option exists for sensitive projects. Price against the hours it actually saves — most developers feel the difference within the first week of real use.

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Ollama FAQs

What is Ollama?

Ollama is the standard open-source tool for running large language models on your own machine. One command downloads and runs models like Llama, Mistral, DeepSeek, Gemma, and Qwen with no cloud account, no per-token fees, and no data leaving the device. It handles model management, quantization, and GPU/CPU memory allocation under the hood, exposes a REST and OpenAI-compatible API for app integrations, and has become the default local backend that AI agents and developer tools target.

What are the main features of Ollama?

Ollama offers One-command local model download and execution, Large registry of open models (Llama, Mistral, Gemma, Qwen, DeepSeek), Automatic quantization to fit consumer hardware, REST API and OpenAI-compatible endpoint on localhost, Cross-platform: macOS, Windows, Linux and GPU acceleration with CPU fallback.

How much does Ollama cost?

Ollama is open source, so the software itself is free to download, use and self-host. Your only costs are the infrastructure you run it on and any paid services you connect to it.

What are the pros and cons of Ollama?

Strengths of Ollama include Free, open-source, fully offline; Zero per-token cost and no data leaves the machine; Huge model library with simple versioning. On the downside, Model quality depends on local hardware; large models need serious RAM/VRAM; No cloud sync or managed scaling; Less guardrailing than managed model APIs.