GPT4All is an open-source software ecosystem that allows anyone to train and deploy **powerful** and **customized** large language models on **everyday hardware**.
Nomic AI oversees contributions to the open-source ecosystem ensuring quality, security and maintainability.
In an effort to ensure cross-operating system and cross-language compatibility, the [GPT4All software ecosystem](https://github.com/nomic-ai/gpt4all)
is organized as a monorepo with the following structure:
- **gpt4all-backend**: The GPT4All backend maintains and exposes a universal, performance optimized C API for running inference with multi-billion parameter transformer decoders.
This C API is then bound to any higher level programming language such as C++, Python, Go, etc.
- **gpt4all-bindings**: GPT4All bindings contain a variety of high-level programming languages that implement the C API. Each directory is a bound programming language. The [CLI](gpt4all_cli.md) is included here, as well.
- **gpt4all-api**: The GPT4All API (under initial development) exposes REST API endpoints for gathering completions and embeddings from large language models.
- **gpt4all-chat**: GPT4All Chat is an OS native chat application that runs on OSX, Windows and Ubuntu. It is the easiest way to run local, privacy aware chat assistants on everyday hardware. You can download it on the [GPT4All Website](https://gpt4all.io) and read its source code in the monorepo.
Explore detailed documentation for the backend, bindings and chat client in the sidebar.
You can find an exhaustive list of supported models on the [website](https://gpt4all.io) or in the [models directory](https://raw.githubusercontent.com/nomic-ai/gpt4all/main/gpt4all-chat/metadata/models.json)
Any model trained with one of these architectures can be quantized and run locally with all GPT4All bindings and in the
chat client. You can add new variants by contributing the gpt4all-backend.
## Frequently Asked Questions
Find answers to frequently asked questions by searching the [Github issues](https://github.com/nomic-ai/gpt4all/issues) or in the [documentation FAQ](gpt4all_faq.md).
It is not advised to prompt local LLMs with large chunks of context as their inference speed will heavily degrade.
You will likely want to run GPT4All models on GPU if you would like to utilize context windows larger than 750 tokens. Native GPU support for GPT4All models is planned.