AA isn't the best way to measure relative cost in real world use because some of those benchmark questions are extremely hard for the models. Some models give up quickly on hard questions, other models spin their wheels for a long time before declaring defeat (or getting the answer on token 200k!).

A useful measure of real world cost (complementary with total cost like they already report, of course) would be "cost for correct answers". You could look at the ratio between the two costs to get a measure of laziness which many would find quite useful.