Ultimately the question is whether there's a pareto optimal point for intelligence models. There's 2 potential worlds:

1. Frontier models are so good that the token cost of an average task becomes miniscule, so users are incentivized to use frontier models because their sheer intelligence makes them cheaper to use.

2. There is a pareto optimal point where even if you spend more on tokens overall profits decrease because token costs rise faster than revenue does.

The "no lab has a clear lead" world leads to 2.