GPT4All is a graphical user interface (GUI) application designed to load and interact with Generative AI models locally on any device. It provides an accessible platform for running large language models (LLMs) without the need for cloud APIs or high-end hardware.
Key Features:
Support for popular LLMs such as Mistral, LLaMA, and DeepSeek
Cross-platform compatibility with Windows, macOS, Linux, and ARM architectures
User-friendly interface with a redesigned chat application
LocalDocs integration for private interaction with personal data
Vulkan optimization for enhanced performance on NVIDIA and AMD GPUs
Installable via winget
Audience & Benefit:
Ideal for developers, researchers, and businesses seeking to integrate AI capabilities locally. GPT4All enables efficient, privacy-focused, and cost-effective use of LLMs directly on standard desktop or laptop hardware, eliminating the need for costly cloud infrastructure.
gpt4all gives you access to LLMs with our Python client around llama.cpp implementations.
Nomic contributes to open source software like llama.cpp to make LLMs accessible and efficient for all.
pip install gpt4all
from gpt4all import GPT4All
model = GPT4All("Meta-Llama-3-8B-Instruct.Q4_0.gguf") # downloads / loads a 4.66GB LLM
with model.chat_session():
print(model.generate("How can I run LLMs efficiently on my laptop?", max_tokens=1024))
October 19th, 2023: GGUF Support Launches with Support for:
Mistral 7b base model, an updated model gallery on our website, several new local code models including Rift Coder v1.5
Nomic Vulkan support for Q4_0 and Q4_1 quantizations in GGUF.
Offline build support for running old versions of the GPT4All Local LLM Chat Client.
September 18th, 2023: Nomic Vulkan launches supporting local LLM inference on NVIDIA and AMD GPUs.
July 2023: Stable support for LocalDocs, a feature that allows you to privately and locally chat with your data.
June 28th, 2023: Docker-based API server launches allowing inference of local LLMs from an OpenAI-compatible HTTP endpoint.
Contributing
GPT4All welcomes contributions, involvement, and discussion from the open source community!
Please see CONTRIBUTING.md and follow the issues, bug reports, and PR markdown templates.
Check project discord, with project owners, or through existing issues/PRs to avoid duplicate work.
Please make sure to tag all of the above with relevant project identifiers or your contribution could potentially get lost.
Example tags: backend, bindings, python-bindings, documentation, etc.
Citation
If you utilize this repository, models or data in a downstream project, please consider citing it with:
@misc{gpt4all,
author = {Yuvanesh Anand and Zach Nussbaum and Brandon Duderstadt and Benjamin Schmidt and Andriy Mulyar},
title = {GPT4All: Training an Assistant-style Chatbot with Large Scale Data Distillation from GPT-3.5-Turbo},
year = {2023},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/nomic-ai/gpt4all}},
}