The GPUs going into data centers aren't the kind that can just be reused by putting them into a consumer PC and playing some video games, most don't even have video output ports and put out FPS similar to cheap integrated GPUs.
And the big ones don't even have typical PCIe sockets, they are useless outside of behemoth rackmount servers requiring massive power and cooling capacity that even well-equipped homelabs would have trouble providing!
I would presume that some tier shaped market will arise where the new cards are used for the most expensive compute tasks like training new models, the slightly used for inference, older cards for inference of older models, or applied to other markets that have less compute demand (or spend less $ per flop, like someone else mentioned).
It would be surprising to me that all this capital investment just evaporates when a new data center gets built or refitted with new servers. The old gear works, so sell it and price it accordingly.
At that point it isn't a $10k card anymore, it's a $5k card. And possibly not a $5k card for very long in the scenario that the market has been flooded with them.
Ah well yes to a degree that’s possible but at least at the moment you’d still be better off buying a $5k Mac Studio if it’s just inference you’re doing
Why would you do that when you can pay someone else to run the model for you on newer more efficient and more profitable hardware? What makes it profitable for you and not for them?
this is the crux. Will these data center cards, if a newer model came out with better efficiency, have a secondary market to sell to?
It could be that second hand ai hardware going into consumers' hands is how they offload it without huge losses.