I am speculating the answer is that "Nvidia just works", where Apple may be more niche & hassle to get working with their preferred frameworks/stacks/tools.
Maybe that, but also the Nvidia chips have *vastly* higher performance (see https://resources.nvidia.com/en-us-grace-cpu/grace-hopper-su...). They claim 4 TB/s memory bandwidth and up to 989 single-precision TFlops in tensor mode (67 TFlops for non-tensor ops).
By contrast, M2 Ultra has 800 GB/s memory bandwidth, 31.6 half-precision TFlops in the Neural Engine, and (extrapolating from https://en.wikipedia.org/wiki/Apple_M2), about 27 single-precision TFlops on the GPU.
So 5x memory bandwidth, more than double generic throughput, and at least 32x peak tensor throughput. Sure, the Mac Studio uses much less power, but depending on the application that usually doesn't make up for the speed difference.
By contrast, M2 Ultra has 800 GB/s memory bandwidth, 31.6 half-precision TFlops in the Neural Engine, and (extrapolating from https://en.wikipedia.org/wiki/Apple_M2), about 27 single-precision TFlops on the GPU.
So 5x memory bandwidth, more than double generic throughput, and at least 32x peak tensor throughput. Sure, the Mac Studio uses much less power, but depending on the application that usually doesn't make up for the speed difference.