But are they actually profitable, or do they employ creative accounting where only parts of overhead expenses are counted against all of inference revenue, similar to what Uber did?

OpenAI's numbers show that they definitely are not profitable on inference, and even worse, revenue growth scaled linearly with inference cost from 2024 to 2025, which means they can't outgrow this problem. See https://www.wheresyoured.at/oai_docs/

Yes I wrote a detailed article about this Forbes claim. https://martinalderson.com/posts/no-it-doesnt-cost-anthropic...

Key points - if you compare it to openrouter costs for ~similar sized models it is ~90% gross margin.

And this claim came from Cursor - not Anthropic!

> Lab executives insist that serving tokens is profitable.

Maybe marginally profitable, but right now they need to give out subsidies for people to use their products (Antigravity, Codex, Claude Code et al) in an actually useful manner that prevents churn and at the scale they need to justify usage growth forecasts, which they need to keep the wheel turning.

Probably if you look at the users who exclusively use the simple chat box interfaces (i.e. ChatGPT, Gemini in UI, Claude in UI) plans it is actually profitable, but I'd also say that's not where most of the usage comes from.

I'd love to actually look at both usage + profitability from each user segment to see if their PxQ growth expectations from non-enterprise usage make any sense.

> Many independent providers price tokens of open-weight models at a fraction of Anthropic's prices.

Are those open-weight models as good as Anthropic? Are they the same parameter class?

The point is that you can’t just serve tokens without also training the next models. It’s an inseparable part of your costs, so naturally you can’t be profitable unless the price you are charging ALSO covers training.

Not counting training models as part of your gross margin is just creative accounting. It's an inherent part of being able to provde the service for OpenAI, Anthropic etc.

Even so, their subscriptions are significantly cheaper than the token pricing via API. So at some point they will need to get rid of subscriptions or increase the subscription prices dramatically... And that's assuming their current token pricing is actually profitable. Which it probably isn't.

Lastly, I would not trust one word that comes out of an executive of an AI company (or any other large company, for that matter).

Do tokens just cover ongoing operating costs, or are they also able to pay back the cost of training that model originally?

So these companies will be profitable if training stops? Is that even a real possibility?

I wouldn't trust those claims from any private companies, even public ones play the most insane tricks in earnings calls to inflate numbers or heck, just make up new ones.

I'm not saying they're wrong, but I don't take much stock in their words.

Buying and driving a new car off the lot costs the manufacturer nothing at that moment, but what happens before that is important to account for.