Knowing the performance is interesting. Apparently it's 1-3 tokens/second.

I guess llama.cpp isn't quite as popular as I had assumed.

I imagine so regarding GPUs, right? Is this is a legitimate project then doesn’t it provide a proof of concept for performance constraints that relate to them? Couldn't the environmentally concerned take this as an indicator that the technology can progress without relying on as much energy is potentially spent now? Shouldn’t researchers in the industry be thinking of ways to prevent the future capabilities of the technology from outrunning the capacity of the infrastructure?

I know very little about AI but these are things that come to mind here for me.

Python and PyTorch all call out to C libraries… I don’t get what he means by “proving LLMs can run without Python and PyTorch” at all. Seems like they don’t understand basic fundamentals about things here…

:D Your code was nicely written and it was a pleasure to port to SIMD because it was already very data-parallel.

> no one uses gemma 3 in prod anyway.

Umm, we do. It's still one of the best for eu countries support / help chatbot style. It's got good (best?) multilingual support ootb, it's very "safe" (won't swear, won't display chinese characters, etc) and it's pretty fast.

I think /* */ single-line comments is a pretty good indication.

Gemma3 is probably the best supported fine tunable model.