Not impossible that the gap will be bridged in the other direction, by GPT-N or a cousin requiring much less VRAM ....

LLaMA already runs on M2 and is comparable to gpt 3

I gave a try at Alpaca-LoRA with tloen's tuning and it definitely feels in reach of GPT 3. Not quite as good, but some of that may just be in whatever's going on with OpenAI's hidden prompts encouraging lots of text out of the model.

Alpaca already works in just 4GB of RAM. This stuff is moving incredibly fast.

It doesn't work well at all. (Also alpaca.cpp uses 8GB of RAM for a 4GB model, possibly because they don't know how mmap works.)

alpaca lora is quite capable actually and is suddenly gaining a hell of a lot of traction in the corporate world

> GPT-3 was said to require something like 150gb of VRAM.

By all accounts GPT-3 is wildly inefficient in resource use; OpenAI runs like a company that’s concerned with the functionality it can achieve by calendar date, and has an almost infinite bankroll to do it. But, other actors in the field have different priorities, and the various open source or, at least, available-to-use models seem to be far more efficient than the OpenAI models of similar function (though they are behind the newest OpenAI models in function.)

Dall-e 2 was claimed to need A100s. Stable Diffusion runs on 6 year old gamer cards.