Not everything is limited by the transfer speed to/from the GPU. LLM inference, for example.
> the hardware wasn't usable on macOS
This eGPU thing is from a third-party if I understand correctly. I don't see why nvidia would get excited about that. If they cared about the platform, they would have released something already.
The software stack has been ready for Apple Silicon for more than a half decade.
The tradeoff vs. a physical eGPU: no Thunderbolt bandwidth ceiling or cabling, but you do need to be on the same LAN and there's ~4% overhead vs. native. Doesn't help if you need the GPU while traveling, and won't fix the physical macOS driver situation for native GPU access.
Disclosure: I work on GPU Go (tensor-fusion.ai/products/gpu-go), so I'm obviously biased toward this approach — but it genuinely is a different point in the design space from eGPU.
At that point you're making more work for yourself than debugging over SSH.