(Of course this all depends on if their plans work out, but if not then the smaller local models will probably play a big role in the failure of their plan)
At API pricing (i.e. what all enterprise customers are paying), inference is profitable, even if they're paying usurious rates on cost of capital for capex. Where the frontier labs are getting screwed is that they're in a Red Queen's race with each other, spending tens of billions of dollars per year training the next frontier model, and not being able to recoup the investment on that model before it's obsolete.
That's why you see the CEOs calling for government intervention to "pace the frontier": it lets them reduce investment on training without risking that their competitors keep going and make them obsolete. Unfortunately for them, the Chinese labs exist, and would love nothing more than to take the frontier, so they're in a bit of a pickle.
However, that also means AI will be even more lobotomized since the cloud providers will panic over being liable
People keep repeating this, but it is only remotely close to true if you evaluate inference in a vacuum without any of the other supporting costs to facilitate that capability.
Just a few years ago people were saying the same thing about WeWork: "leasing is profitable, the unit economics of individual locations is net positive", and yet...