I want to buy a new GPU mainly for SD. The machine-learning space is moving quickly so I want to avoid buying a brand new card and then a fresh model or tool comes out and puts my card back behind the times. On the other hand, I also want to avoid needlessly spending extra thousands of dollars pretending I can get a ‘future-proof’ card.
I’m currently interested in SD and training LoRas (etc.). From what I’ve heard, the general advice is just to go for maximum VRAM.
- Is there any extra advice I should know about?
- Is NVIDIA vs. AMD a critical decision for SD performance?
I’m a hobbyist, so a couple of seconds difference in generation or a few extra hours for training isn’t going to ruin my day.
Some example prices in my region, to give a sense of scale:
- 16GB AMD: $350
- 16GB NV: $450
- 24GB AMD: $900
- 24GB NV: $2000
edit: prices are for new, haven’t explored pros and cons of used GPUs
Good to know about CUDA/Direct ML.
I found a couple of 2022 posts recommending 3090s, especially since cryptocoin miners were selling lots of them cheap. Thanks for the heads up about the 5000 release, I suspect it will be above my budget but it will net me better deals on a 4090 :P
Yeah I don’t think 4090 is going down in price. As of now, they’re more expensive than even they launched and it seems production is ramping down.
DirectML sucks but ROCm is great, but you need to check if the software you want to use works with ROCM. Also note there’s only like 4 cards that work with ROCm as well.