It's well know everyone is making great money on inference. The cost is training.

Whether GPT-5 was profitable to run depends on which profit margin you’re talking about. If we subtract the cost of compute from revenue to calculate the gross margin (on an accounting basis),2 it seems to be about 30% — lower than the norm for software companies (where 60-80% is typical) but still higher than many industries.

(They go on to point out that there are other costs that might mean they didn't break even on other costs - although I suspect these costs should be partially amortized over the whole GPT 5.x series, not just 5.0)

https://epochai.substack.com/p/can-ai-companies-become-profi...

https://martinalderson.com/posts/are-openai-and-anthropic-re... (with math working backwards from GPU capacity)

"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"

https://simonwillison.net/2025/Aug/17/sam-altman/

"There’s a bright spot, however. OpenAI has gotten more efficient at serving paying users: Its compute margin—the revenue left after subtracting the cost of running AI models for those customers—was roughly 70% in October, an increase from about 52% at the end of last year and roughly 35% in January 2024."

https://archive.is/OqIny#selection-1279.0-1279.305 (Note this is after having to pay higher spot rates for compute because of higher than expected demand)

> It's well know everyone is making great money on inference.

That is not, in fact, "well known", but based entirely on the announcements of the inference providers themselves who also get very cagey when asked to show their work and at least look like they're soliciting a constant firehose of investment money simply to keep the lights on. In particular there's a troubling tendency to call revenue "recurring" before it actually, you know, recurs.