I don’t have any Nvidia GPUs to compare to so my only comparison is Colab Pro and CPUs.
The M1 Max with 32 GPU cores generally performs about 4 times faster than the M1 in my testing - just as you would expect. It is sometimes a closer to 5x in some cases which I am guessing is related to unified memory but that is a guess and I am far from an expert in hardware optimisation for ML.
For very small image sizes and very small batch sizes, the M1 Max GPU (and M1) don’t really offer much (but the CPU performs well in those cases). When the batch and image sizes get larger the M1 Max starts to kick in.
When compared to Colab Pro (P100 GPU), the M1 Max was 1-1.25x the speed of Colab Pro. For me that works well because it means that I can train models that take a longer time without worrying about timeouts. However, from other posts it sounds like an RTX6000 could make everything significantly faster. However, it is not practical for me to get a separate system with an RTX6000 (as the card itself costs more than my entire M1 Max computer).
I guess my summary is that the M1 Max seems like a reasonable medium level system - significantly faster than similarly priced systems but not in the same league as higher cost setups.