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Ollama

Run local LLMs on your machine

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Local chatbot
Model testing
Ollama lets you run large language models on your own machine. You download and manage models through a simple command line interface. The tool keeps your data private since prompts never leave your computer when running local models.
Screenshot of the homepage of ollama.com

AI tool Advantages icon Advantages

  • Runs models locally and privately
  • Free for local model usage
  • Supports over 100 models

AI tool disadvantages icon Disadvantages

  • Requires sufficient hardware resources
  • Less control than llama.cpp
  • Cloud direction sparked privacy concerns

Plans and pricing icon Plans and pricing

  • Free
  • $20 per month
  • $100 per month

Open Source

Yes

Most suitable professions

YouTube video Video

Use cases

  • Run chatbots on your hardware
  • Build AI apps with local models
  • Test and compare open models
  • Code assistance via local API

Target audience

  • Developers
  • AI researchers
  • DevOps engineers
  • Privacy-conscious users
  • Hobbyists and tinkerers

HDRobots review of the AI tool HDRobots review

Ollama is an open source tool that lets you run large language models on your own hardware. You install it on macOS, Windows, or Linux, then pull models by name and run them with simple commands. It handles model weights, configurations, and GPU acceleration so you can focus on using the models rather than configuring them.

The tool supports a library of over 100 models including Llama, Mistral, Qwen, and others. You can run multiple models at the same time, and it manages memory allocation between them. An OpenAI-compatible API means you can swap local models into existing applications with minimal code changes.

Ollama added optional cloud features in 2025, letting you access larger models on datacenter hardware when your local machine is not powerful enough. Local use remains free. The Pro tier costs $20 per month and the Max tier costs $100 per month for higher cloud usage limits. Some users have raised concerns about the cloud direction, preferring the tool stay focused on local-only functionality.

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