GPT Features

Owned by Support User
Last updated: Dec 11, 2023
2 min read

There are several reasons why you might want to use GPT4All over ChatGPT.

 

  • Portability: Models provided by GPT4All only require four to eight gigabytes of memory storage, do not require a GPU to run, and can easily be saved on a USB flash drive with the GPT4All one-click installer. This makes GPT4All and its models truly portable and usable on just about any modern computer out there.

  • Privacy and Security: As explained earlier, unless you have access to ChatGPT Plus, all your ChatGPT conversions are accessible by OpenAI. GPT4All is focused on data transparency and privacy; your data will only be saved on your local hardware unless you intentionally share it with GPT4All to help grow their models.

  • Offline Mode: GPT is a proprietary model requiring API access and a constant internet connection to query or access the model. If you lose an internet connection or have a server problem, you won't have access to ChatGPT. This is not the case with GPT4All. Since all the data is already stored on a four to eight-gigabyte package, and inferencing is done locally, you do not require an internet connection to access any models in GPT4All. You can continue chatting and fine-tuning your model even without an internet connection.

  • Free and Open Source: Several LLMs provided by GPT4All are licensed under GPL-2. This allows anyone to fine-tune and integrate their own models for commercial use without needing to pay for licensing.

 

GPT4All is an ecosystem used to train and deploy LLMs locally on your computer, which is an incredible feat! Typically, loading a standard 25-30GB LLM would take 32GB RAM and an enterprise-grade GPU.

To compare, the LLMs you can use with GPT4All only require 3GB-8GB of storage and can run on 4GB–16GB of RAM. This makes running an entire LLM on an edge device possible without needing a GPU or external cloud assistance.

The hardware requirements to run LLMs on GPT4All have been significantly reduced thanks to neural network quantization. By reducing precision weight and activations in a neural network, many of the models provided by GPT4All can be run on most relatively modern computers.

The training data used in some of the available models were collected through "the pile," which is just scraped data from publicly released content on the internet. The data is then sent to Nomic AI's Atlas AI database, which can be seen based on correlations on an easy-to-see 2D vector map (also known as an AI vector Databases).