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Inference is quite profitable, so wrong again.
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Right. Going to take "inference is quite profitable" apart, because there's nothing else in your reply.

OpenAI's adjusted gross margin: 40% in 2024, 33% in 2025. Reason cited: inference costs quadrupled in one year.

https://sacra.com/c/openai/

Internal projections leaked to The Information: ~$14B loss on ~$13B revenue in 2026. Cumulative losses through 2028: ~$44B.

https://finance.yahoo.com/news/openais-own-forecast-predicts...

A business burning more than a dollar for every dollar of revenue is a lot of things. "Quite profitable" is not one of them.

If you're reaching for the SaaStr piece on API compute margins hitting ~70% by late 2025: yes, that exists, and it describes one tier. The volume is on the consumer side. The consumer side is the bit on fire. Pointing at the API margin and calling the whole business profitable is the financial equivalent of weighing yourself with one foot off the scale.

The original argument, in case it got lost: Microsoft holds (held) a 49% stake in a company projecting another $44B of cumulative losses through 2028, against unit economics that depend on competitors not catching up. That's textbook hedge-the-bet territory. "They have paying customers" doesn't refute that, MoviePass had paying customers too.

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Pointing at the API margin and calling the whole business profitable is the financial equivalent of weighing yourself with one foot off the scale.

I didn’t call the business profitable, I said that inference is profitable. I was responding to your assertion that they’re speculating by selling below cost. Which isn’t true; they’re selling inference, profitably. They’re losing money because they’re investing in the next model. The company isn’t profitable, it might never be profitable, but the product they’re selling is profitable. So calling it speculation based on selling something below cost is just factually incorrect.

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Granted on the narrow point: inference itself runs at a positive margin. Where it falls apart is the implicit claim that the training spend is separable.

It isn't. Frontier model training is the cost of having a product to sell inference on next year. Stop training and the inference margin decays on the timescale of the next competitor release, which in 2026 is measured in weeks. So "the product is profitable, the company is just investing" describes a business where the investment is structurally non-optional and structurally larger than the product margin. That's the definition of selling below cost at the level that matters, which is the level you're hedging at when you hold 49%.

McDonald's is profitable because a Big Mac in 2027 costs roughly what a Big Mac in 2026 cost to make. OpenAI's product depreciates to zero on a 12-month cycle unless they spend ~$40B keeping it ahead. That's the disagreement, and "but inference itself has positive margin" doesn't resolve it, it just relocates it.

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