> It's widely understood that the big players are making profit on inference.

If you add in the cost of training, it’s not profitable.

Not including the cost of training is a bit like saying the only cost of a cup of coffee is the paper cup it’s in. The only way OpenAI gets to charge for inference is by selling a product people can’t get elsewhere for much cheaper, which means billions in R&D costs. But because of competition, each model effectively has a “shelf life”.

At least Anthropic claims that they are profitable on a per model basis. But since both revenue and training costs are growing exponentially, and they need to pay for model N training today, and only get revenue for model N-1 today, the offset makes it look worse than it is.

Obviously that doesn’t help them turn a profit, until they can stop growing training costs exponentially.

So it’s really a race to see whether growth in revenue or training costs decelerates first.