For the top few providers, the training is getting amortized over absurd amount of inference. E.g. Google recently mentioned that they processed 980T tokens over all surfaces in June 2025.
The leaked OpenAI financial projections for 2024 showed about equal amount of money spent on training and inference.
Amortizing the training per-query really doesn't meaningfully change the unit economics.
> Fact remains when all costs are considered these companies are losing money and so long as the lifespan of a model is limited it’s going to stay ugly. Using that apartment building analogy it’s like having to knock down and rebuild the building every 6 months to stay relevant. That’s simply not a viable business model.
To the extent they're losing money, it's because they're giving free service with no monetizaton to a billion users. But since the unit costs are so low, monetizing those free users with ads will be very lucrative the moment they decide to do so.
Assuming users accept those ads. Like, would they make it clear with a "sponsored section", or would they just try to worm it into the output? I could see a lot of potential ways that users reject the ad service, especially if it's seen to compromise the utility or correctness of the output.
Billions of people use Google, YouTube, Facebook, Tiktok, Instagram, etc and accept the ads. Getting similar ad rates would make OpenAI fabulously profitable. They have no need to start with ad formats that might be rejected by users. Even if that were the intended endgame, you'd want to boil the frog for years.