Generative AI Is an Engineering Disaster. A shockingly inefficient trillion-dollar project.
a month ago by Some_Emo_Chick to c/technology
Actually still no
https://github.com/JustVugg/colibri
Everyone was desperate to be first because capitalism. But we are getting good models without the insane build out requirement. Which will be hilarious to leave the cunts holding the bag. Not that the planet is better for it in the end.
~1 token per second (storage bound gen4 nvme)... Some of us have places to be.
Don't get me wrong. Its impressive that it can run at all, but honestly the usecase is exceedingly narrow. You'd have better results with a structured quantized gpu-only gemma or qwen workflow. Quality over quantity, rely on validation and a structured process: lots of cross-model review and iteration loops with spec and test driven dev. You could probably get a working alpha by the time colibri set up the environment.
Yeah I'm just beginning my local AI journey on a 5080, tried Qwen3.6 27b Q4 and was getting like 1tps because of the vram overflow. Ran it over night at it was still chewing on generating a prompt for a sub agent when I got up in the middle of the night until it simply ended in some kind of "fetch failure" lol. I think I gave it something too large to tackle, but either way 1tps is kinda garbage.
Is that quantized? 4 bit Qwen 3.6 can get 22tps on a 1060.
What are you using to run the model? Llama.cpp will automatically split the model between your system ram and graphics card's vram.
Qwen 3.6 is a mixture of experts model with only 3B parameters active at a time. Even without quantization your card could easily run that.
@lemmy.world
go to feed...
@lemmy.world
go to feed...
But it’s so good at programming if you already know how to program! Surely that’s worth burning the planet and crashing the world economy??
save