For inference or training? For training, Apple has no CUDA, so you're pretty much dead in the water, unless you're specifically interested in e.g. local fine-t

For inference or training? For training, Apple has no CUDA, so you're pretty much dead in the water, unless you're specifically interested in e.g. local fine-tuning (for e.g. privacy or start-up strategy of "use the user's compute"). For inference, 4090 and H100 are not designed for throughput per $. Nvidia GPUs like the A40 or T40 are tuned for cloud inference, but at the end of the day your product is either running inference server-side (so play your own CAPEX vs OPEX, maybe even try Jetson) or user-side and so the user chooses the hardware not you. I mean maybe there are Wallstreet analysts or people at Qualcomm/Broadcom who want an Apple vs Nvidia shootout to see who is getting the most of their silicon, but for the product space the comparison is basically irrelevant. Which is likely what Apple and Nvidia want right now.