That's my point; if silicon demand shits from mobile to AI data centers you can't expect energy consumption to be the same.
Demand right now is not shifting from mobile to datacenter, demand is shifting from "normal" datacenter compute to AI datacenter compute.
I think if you had said "AMD Epyc" rather than a mobile chip, that would be a much more apt comparison. The AI chips are somewhat more power intensive per box, but fairly similar on power/area. It turns out that these silicon processes are fairly uniform in terms of the power/area that they can sustain for any kind of workload.
Mobile chips are designed for <10% utilization and "rush-to-idle" workloads, and they are not remotely comparable to datacenter silicon (of any kind).
A16 is 200 sq mm of silicon while an H100 is about 800. That means you get about 100-120 A16's on a wafer, while you only get ~30 H100's (see https://www.silicon-edge.co.uk/j/index.php/resources/die-per...).
Let's assume yield is 100% to make things easier. The rated max power of the A16 is about 250W, while the H100 is quoted at 700W. Thus, a wafer of A16's is about 25-30 kW of power, while a wafer of H100's is about 21 kW.
Edit: Just clarifying, this is not about the Apple A16, but the Nvidia A16. The mobile process used by the Apple chips is built for much lower performance and power, so I can't imagine the two chips being anywhere near comparable - they fill two completely different roles.