And again, no. The cost of inference is a function of the size of the model and if models keep getting bigger, deeper, badder, the cost of inference will keep going up. And if models stop getting bigger because improved performance can be achieved just by scaling inference, without scaling the model- well that's still more inference; and even if the cost overall falls, there will need to be so much more inference to scale sufficiently to keep AI companies in competition with each other that the money they have to spend will keep increasing, or in other words it's not how much it costs but how much you need to buy.
This is a thing, you should know. It's called Jevon's Paradox:
In economics, the Jevons paradox (/ˈdʒɛvənz/; sometimes Jevons effect) occurs when technological progress increases the efficiency with which a resource is used (reducing the amount necessary for any one use), but the falling cost of use induces increases in demand enough that resource use is increased, rather than reduced.[1][2][3][4]
Inference always starts expensive. It comes down.