It's less of a "performance falls off a cliff" problem and more of a "once you offload to RAM/storage, your bottleneck is the RAM/storage and basically everything else no longer matters". This means if you know you're going to be relying on heavy offload, you stop optimizing for e.g. lots of VRAM and GPU compute since that doesn't matter. That saves resources that you can use for scaling out.

It depends on the model and the mix. For some MoE models lately it’s been reasonably fast to offload part of the processing to CPU. The speed of the GPU still contributes a lot as long as it’s not too small of a relative portion of compute.