I would bet money Anthropic and OpenAI are actually profitable on inference. The problem is they have to spend large sums of money to train models that are essentially worthless after a few months.
They make more money from inference than they do training the model, but then the next model gets so much more expensive to train so their annual figures have been in the red.
One could say "that's a great point, we should take more direct ideological action to address this issue!", but expounding upon the finer details would likely get one banned here.
API pricing isn’t cost, we don’t know what cost is.
I would bet money Anthropic and OpenAI are actually profitable on inference. The problem is they have to spend large sums of money to train models that are essentially worthless after a few months.
Dario explicitly stated this in an interview.
They make more money from inference than they do training the model, but then the next model gets so much more expensive to train so their annual figures have been in the red.
So, it's like if they were a pharma company that was barely profitable if you didn't take into account R&D costs?
A large part of the GPT-5.x model iteration has been about making training more affordable and token efficient.
It's to build a moat, of course!
Narrator: there was no moat
This performative concern over token costs and subsidisation comes from either ignorance or some latent ideology signalling.
One could say "that's a great point, we should take more direct ideological action to address this issue!", but expounding upon the finer details would likely get one banned here.