Is there a reason not to think that, when "refining" the models they're using the benchmarks as the measure and it shows no fidelity loss but in some unbenchmarked ways, the performance is worse. "Once a measure becomes a target, it's no longer a useful measure."

That's case #2 for you but I think the explanation I've proposed is pretty likely.