Oh I know for sure, it's still just amusing to me to look up these just slightly older cards and see them going for so little compared to what they were new; I

Oh I know for sure, it's still just amusing to me to look up these just slightly older cards and see them going for so little compared to what they were new; I do also look at various benchmarks and comparisons over and over because I would like to build a home gpu server for some machine learning fun and I find it interesting that the TFLOPS/$ numbers always come out very much linear... A card that gives 2x performance costs 2x more.... if cards depreciate 50%, it's because new cards have been launched that have double performance for the same price... etc... Even simpler, the CUDA cores-per-dollar is pretty much a constant. What isn't taken into account there is various optimizations new cards have that speed up training or inference, like better use of the tensor cores. At some point incompatibility with newer CUDA compute levels makes the older cards much less useable.