GPU | VRAM | Price (€) | Bandwidth (TB/s) | TFLOP16 | €/GB | €/TB/s | €/TFLOP16 |
---|---|---|---|---|---|---|---|
NVIDIA H200 NVL | 141GB | 36284 | 4.89 | 1671 | 257 | 7423 | 21 |
NVIDIA RTX PRO 6000 Blackwell | 96GB | 8450 | 1.79 | 126.0 | 88 | 4720 | 67 |
NVIDIA RTX 5090 | 32GB | 2299 | 1.79 | 104.8 | 71 | 1284 | 22 |
AMD RADEON 9070XT | 16GB | 665 | 0.6446 | 97.32 | 41 | 1031 | 7 |
AMD RADEON 9070 | 16GB | 619 | 0.6446 | 72.25 | 38 | 960 | 8.5 |
AMD RADEON 9060XT | 16GB | 382 | 0.3223 | 51.28 | 23 | 1186 | 7.45 |
This post is part “hear me out” and part asking for advice.
Looking at the table above AI gpus are a pure scam, and it would make much more sense to (atleast looking at this) to use gaming gpus instead, either trough a frankenstein of pcie switches or high bandwith network.
so my question is if somebody has build a similar setup and what their experience has been. And what the expected overhead performance hit is and if it can be made up for by having just way more raw peformance for the same price.
Your math checks out, but only for some workloads. Other workloads scale out like shit, and then you want all your bandwidth concentrated. At some point you’ll also want to consider power draw:
Now include power and cooling over a few years and do the same calculations.
As for apples and oranges, this is why you can’t look at the marketing numbers, you need to benchmark your workload yourself.