Good. Maybe we can get some sanely priced GPUs now.
Everyone I know who’s bought a GPU recently has gone used, including me
That and there just hasn’t been much gains in performance in recent years, so it makes sense to not upgrade for a while. And a lot of people upgraded all at once during the pandemic, so there are less people on the market for a new GPU.
I got a prebuilt like a couple years ago after getting a chunk of money and it still does me ok. There’s a 6800xt in it and it still handles current games ok. I’m in no rush, the only thing I would like is better ray tracing but that’s not enough of a reason for me to spend £700+ on a new card.
Very true, I was using a 1080TI until a few months ago.
Not me, but looking at prices, the $500 I paid for my 6950 beats a lot of used prices out there now
What sort of discount on retail did you get?
Bring back 3dfx Voodoo you cowards.
At this point, emulating or using a wrapper for 3dfx is not gonna make any game that needs it run bad. Don’t really need the “full speed” of native support anymore.
If you have something from the Nvidia rtx20xx generation or newer, I’m not sure how much advantage there is to upgrading at all.
What’s NVidia seeing in the gaming space? Or do they conflate gaming and ML sales?
Who would buy consumer grade hardware for machine learning?
Almost everyone?
There are many different niches of ML. 99% of hobbyist would use consumer grade hardware. It’s quite frankly more than good enough.
Even in commercial usage, consumer GPUs provide better value unless you need to do something that very specifically require a huge vram pool. Like connecting multiple A100 GPUs to have hundreds or tens of thousands of gigabyte vram. Those use cases only come up if you’re making base models for general purpose.
If you’re using it for single person use case, something like 4090 is actually the best hardware. Enough ram to run almost anything and it’s higher clock speed than enterprise GPU means your results come back faster.
Even training doesn’t require that much vram. Chat models are generally more vram heavy but if you’re doing specific image training like stable diffusion for how to render your face, or some specific fetish porn, you only really need like 12GB of vram to do it. There are ways to even do it at lower like 8GB but 12 is sweet value spot where even 3060 or 4060ti can do. Consumer GPUs will get that trained in like 30min to 24hrs depending on settings and model.
If you want to get started in machine learning cheap and want something faster than cpu training, a 1080ti goes for $120 or so on ebay.
