I did a quick research. ChatGPT still has way, way more parameters.

- ChatGPT-3.5, and GPT-4 are Large Language Models (LLMs) ChatGPT has 175 billion parameters

> Parameters including weights and biases.

>The numbers of parameters in a neural network is directly related to the number of neurons and the number of connections between them.

>Needs supercomputers for training and inference

- LLaMA (by Facebook): Open and Efficient Foundation Language Models

>[llama.cpp](https://github.com/ggerganov/llama.cpp)

> a collection of foundation language models ranging from 7B to 65B parameters

> Facebook says LLaMA-13B outperforms GPT-3 while being more than 10x smaller

> If it is 10x smaller then we don't need a supercomputer

- alpaca.cpp (Stanford Alpaca is an instruction-following LLaMA model)

> It is a fine-tuned version of Facebook's LLaMA 7B model

> It is trained on 52K instructions-following demonstrations.

> uses around 4GB of RAM.