Are OpenAI and Anthropic losing money on inference?

https://www.axios.com/2025/08/15/sam-altman-gpt5-launch-chat... quotes Sam Altman saying:

> Most of what we're building out at this point is the inference [...] We're profitable on inference. If we didn't pay for training, we'd be a very profitable company.

ICYMI, Amodei said the same in much greater detail:

"If you consider each model to be a company, the model that was trained in 2023 was profitable. You paid $100 million, and then it made $200 million of revenue. There's some cost to inference with the model, but let's just assume, in this cartoonish cartoon example, that even if you add those two up, you're kind of in a good state. So, if every model was a company, the model, in this example, is actually profitable.

What's going on is that at the same time as you're reaping the benefits from one company, you're founding another company that's much more expensive and requires much more upfront R&D investment. And so the way that it's going to shake out is this will keep going up until the numbers go very large and the models can't get larger, and then it'll be a large, very profitable business, or, at some point, the models will stop getting better, right? The march to AGI will be halted for some reason, and then perhaps it'll be some overhang. So, there'll be a one-time, 'Oh man, we spent a lot of money and we didn't get anything for it.' And then the business returns to whatever scale it was at."

https://cheekypint.substack.com/p/a-cheeky-pint-with-anthrop...

The "model as company" metaphor makes no sense. It should actually be models are products, like a shoe. Nike spends money developing a shoe, then building it, then they sell it, and ideally those R&D costs are made up in shoe sales. But you still have to run the whole company outside of that.

Also, in Nike's case, as they grow they get better at making more shoes for cheaper. LLM model providers tell us that every new model (shoe) costs multiples more than the last one to develop. If they make 2x revenue on training, like he's said, to be profitable they have to either double prices or double users every year, or stop making new models.

>Also, in Nike's case, as they grow they get better at making more shoes for cheaper.

This is clearly the case for models as well. Training and serving inference for GPT4 level models is probably > 100x cheaper than they used to be. Nike has been making Jordan 1's for 40+ years! OpenAI would be incredibly profitable if they could live off the profit from improved inference efficiency on a GPT4 level model!

>>This is clearly the case ... probably

>>OpenAI would be incredibly profitable if they could live off the profit from improved inference efficiency on a GPT4 level model!

If gpt4 was basically free money at this point it's real weird that their first instinct was to cut it off after gpt5

> If gpt4 was basically free money at this point it's real weird that their first instinct was to cut it off after gpt5

People find the UX of choosing a model very confusing, the idea with 5 is that it would route things appropriately and so eliminate this confusion. That was the motivation for removing 4. But people were upset enough that they decided to bring it back for a while, at least.

They picked the worst possible time to make the change if money wasn’t involved (which is why I assumed GPT-5 must be massively cheaper to run). The backlash from being forced to use it cost a fair bit of the model’s reputation.