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Website • Documentation • Discord • YouTube Tutorial

GPT4All runs large language models (LLMs) privately on everyday desktops & laptops.

No API calls or GPUs required - you can just download the application and get started.

Read about what's new in our blog.

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GPT4All is made possible by our compute partner Paperspace.

— Windows Installer —

— Windows ARM Installer —

— macOS Installer —

— Ubuntu Installer —

The Windows and Linux builds require Intel Core i3 2nd Gen / AMD Bulldozeror better.

The Windows ARM build supports Qualcomm Snapdragon and Microsoft SQ1/SQ2 processors.

The Linux build is x86-64 only (no ARM).

The macOS build requires Monterey 12.6 or newer. Best results with Apple Silicon M-series processors.

See the full System Requirements for more details.

Flathub (community maintained)

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))

🦜🔗 Langchain 🗃️ Weaviate Vector Database - module docs 🔭 OpenLIT (OTel-native Monitoring) - Docs

• July 2nd2024: V3.0.0 Release
  • Fresh redesign of the chat application UI
  • Improved user workflow for LocalDocs
  • Expanded access to more model architectures
• October 19th2023: GGUF Support Launches with Support for:
  • Mistral 7b base modelan updated model gallery on our websiteseveral 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 18th2023: Nomic Vulkan launches supporting local LLM inference on NVIDIA and AMD GPUs.
• July 2023: Stable support for LocalDocsa feature that allows you to privately and locally chat with your data.
• June 28th2023: Docker-based API server launches allowing inference of local LLMs from an OpenAI-compatible HTTP endpoint.

GPT4All welcomes contributionsinvolvementand discussion from the open source community! Please see CONTRIBUTING.md and follow the issuesbug reportsand PR markdown templates.

Check project discordwith project ownersor 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: backendbindingspython-bindingsdocumentationetc.

If you utilize this repositorymodels or data in a downstream projectplease 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- 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}},
}