the H200 has a very impressive bandwith of 4.89 TB/s, but for the same price you can get 37 TB/s spread across 58 RX 9070s, but if this actually works in practice i don’t know.

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:

• One H200 is like 1500W when including support infrastructure like networking, motherboard, CPUs, storage, etc.
• 58 consumer cards will be like 8 servers loaded with GPUs, at like 5kW each, so say 40kW in total.

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.

Well, a few issues:

• For hosting or training large models you want high bandwidth between GPUs. PCIe is too slow, NVLink has literally a magnitude more bandwidth. See what Nvidia is doing with NVLink and AMD is doing with InfinityFabric. Only available if you pay the premium, and if you need the bandwidth, you are most likely happy to pay.
• Same thing as above, but with memory bandwidth. The HBM-chips in a H200 will run in circles around the GDDR-garbage they hand out to the poor people with filthy consumer cards. By the way, your inference and training is most likely bottlenecked by memory bandwidth, not available compute.
• Commercially supported cooling of gaming GPUs in rack servers? Lol. Good luck getting any reputable hardware vendor to sell you that, and definitely not at the power densities you want in a data center.
• TFLOP16 isn’t enough. Look at 4 and 8 bit tensor numbers, that’s where the expensive silicon is used.
• Nvidias licensing agreements basically prohibit gaming cards in servers. No one will sell it to you at any scale.

For fun, home use, research or small time hacking? Sure, buy all the gaming cards you can. If you actually need support and have a commercial use case? Pony up. Either way, benchmark your workload, don’t look at marketing numbers.

Is it a scam? Of course, but you can’t avoid it.