Interesting. New models are estimated at ~5T params, so 45,000x increase over BERT base (110m). But vocab size of 200k, so only an increase of 7x over BERT base (30k).
BERT is not an LLM, it's an encoder-only model, i.e. it doesn't generate new text. the first somewhat useful publicly accessible LLM was GPT-3 with 175B params, and it was also the last frontier model whose parameter count was disclosed.