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GPT4All

GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use.

Pricing
Free

About GPT4All

GPT4All is an open-source project from Nomic AI for people who want to run large language models privately on their own desktop or laptop, instead of sending data to a cloud API. It targets both everyday users who just want to download an installer and chat, and developers who want a Python client around local LLMs.

A user downloads a Windows, macOS, or Ubuntu installer, or installs the Python package with pip, and loads a model such as a Llama 3 GGUF file to chat locally. Under the hood it uses a Python client built around llama.cpp implementations, and Nomic contributes upstream to llama.cpp to keep local inference efficient.

GPT4All includes LocalDocs, a feature for privately and locally chatting with a user's own documents, a Docker-based API server that exposes local models through an OpenAI-compatible HTTP endpoint, and Nomic Vulkan support for running local inference on NVIDIA and AMD GPUs. It integrates with Langchain and the Weaviate vector database, and supports GGUF model files including Mistral 7B and DeepSeek R1 distillations.

GPT4All is released under the MIT license and is free to use, including for commercial purposes. It has more than 77.3k GitHub stars and 8.3k forks, and its Windows and Linux builds require an Intel Core i3 2nd Gen or AMD Bulldozer processor or better, while the macOS build requires Monterey 12.6 or newer.

Use cases

  • Chatting privately with local documents
  • Running local LLM inference without GPUs or cloud APIs

Key features

  • Runs LLMs locally with no API calls or GPU required
  • Desktop installers for Windows, macOS, and Ubuntu
  • Python client for local LLM inference
  • LocalDocs for privately chatting with your own files
  • Docker-based OpenAI-compatible API server
  • GPU acceleration via Nomic Vulkan on NVIDIA and AMD cards
  • Integrations with Langchain and Weaviate

Pros and cons

Pros

Free, open source, and usable commercially
No API calls or GPU required to get started
Very widely used, with over 77.3k GitHub stars

Cons

Windows and Linux builds need an Intel Core i3 2nd Gen/AMD Bulldozer or better processor
macOS build requires Monterey 12.6 or newer
Linux build is x86-64 only, no ARM support

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