Users are paying way more than the cost of inference. Look up inference prices of high end open weight models vs claude or gpt. Cheaper by an order of magnitude.
It’s the constant training of new models that’s losing them money. New version is out every month.
To clarify, AI companies charging the cost that would make the inference profitable for them, against the operating costs and financing costs on new capital expenditures (new data centres, new compute and new model training*), is more than what most people appear to be willing to pay. That cost is indeed more than just the cost of inference incurred by the AI company.
*(I’m being generous and including model training as capex for the sake of argument, even if I personally think to continue the hypetrain, continuous model improvements are core to AI companies’ operation.)
Users are paying way more than the cost of inference. Look up inference prices of high end open weight models vs claude or gpt. Cheaper by an order of magnitude.
It’s the constant training of new models that’s losing them money. New version is out every month.
To clarify, AI companies charging the cost that would make the inference profitable for them, against the operating costs and financing costs on new capital expenditures (new data centres, new compute and new model training*), is more than what most people appear to be willing to pay. That cost is indeed more than just the cost of inference incurred by the AI company.
*(I’m being generous and including model training as capex for the sake of argument, even if I personally think to continue the hypetrain, continuous model improvements are core to AI companies’ operation.)