Because all the variables that go into performance / efficiency measurement of a model (processing power, algorithm efficiency, parallelization, etc) boil down to cost per token input and token output. And the tangible cost for a datacenter is power consumed. Of course, amortized capex costs are also part of the game.

Maybe it's just because the specifics on FLOPs are more complicated, especially given how many different floating point formats are floating around in ML. Even NVIDIA has like 6 different FLOPs numbers on their GPUs nowadays.

Some of it might be market-signaling to the broader energy industry: "hey would you PLEASE build more power plants and power lines? Look at all this money we have, we will pay for it!"

It's more meaningful to most people than FLOPS/other measures of actual computing power.

It's easy to think about. Google reported a global average power consumption of 3.7GW in 2024, so you can think of this deal as representing an expansion of something like 10-15% of that 2024 baseline, if you assume 50% capacity utilization.

Because that’s the limiting factor