Don’t have direct experience with either, but:
It’s my understanding that a corral tpu is exclusively an inference accelerator, no training or more generative applications. Also, corral TPUs are a little bit unobtainium, with the only options I’ve seen behind scalped about as much as a pi, to basically the same result.
I think you’re overthinking the nano a bit. I’m not sure that you’d need explicit support for the nano, because it’s just a cuda gpu and so it should^TM just run anything cuda, as long as the arm cpu doesn’t trip the software up . For example, I’ve seen people running blender renders across a cluster of jetsons, just because, and I doubt that blender has any explicit support for jetsons.
If you’re coming at it from the sense that you have rack space to spare, a used Tesla / Quadro gpu would probably be better value than a jetson nano OG, because those were I think 2GB/4GB and 256 Kepler era cuda cores. You’d almost have to go out of your way to find a worse PCIe card, plus a normal PCIe card in a normal x86 server wouldn’t have arm software restrictions. Although as the other commenter mentioned, cooling/power draw is a more serious consideration for a PCIe card, plus the risks of buying used.
Alternatively, they could have gotten a new name to make sure people don’t buy the old one by mistake. Idk, just a thought.