It pretty much comes down to 2 factors which is memory bandwidth and compute. You need a high enough memory bandwidth to be able to "feed" the compute and you need beefy enough compute to be able to keep up with the data that is being fed in by the memory. In theory a single Nvidia 4090 would be able to run a 70b model with quantization at "useable" speeds. The reason mac hardware is so capable in AI is because of the unified architecture meaning the memory is shared across the GPU and CPU. There are other factors but it essentially comes down to tokens per second advantages. You could run one of these models on an old GPU with low memory bandwidth just fine but your tokens per second would be far too slow for what most people consider "useable" and the quantization necessary might star noticeably effecting the quality.