Anthropic and OpenAI make money on API calls, margins have been reported in public filings. Subs are subsidized.

That's not possible, read my comment above. These are private companies, there are no public filings regarding their profitability in any sense. You're just making things up.

If you have a machine running at 150 tok/ps you can only make $5820 a month at $15 per 1mm running 24/7. It costs a hell of a lot more than 6k a month to run Claude 4.7 @ 150 tok/ps on that machine 24/7.

This math is a bit off, because you have input tokens too, but regardless its still not profitable especially for how long it takes to turn around a request and the caching is probably not all that profitable.

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mtone 4 hours ago | parent [-]

You're forgetting a critical factor: concurrency. If a given hardware serves a single request at 150 tokens/s, it can also serve 20-30 requests at 100 tokens/s. Suddenly your $5K becomes $100K/month, enough to recoup the cost of the hardware in a year or so.

The reason it works: each time you read the model (memory bound) to calculate the next token, you can also update multiple requests (compute bound) while at it. It's also much more energy-efficient per token.

[1] https://aimultiple.com/gpu-benchmark

	▲	dakolli 3 hours ago \| parent [-]
		Interesting I didn't know about this, but it makes sense after reading the article. They are benchmarking on a single GPU on a 20bb param model. Does it scale across 60 H100s over NVLink/NVSwitch. I would be interested to see those benchmarks. The idea that everyone is spinning up a $2 million in GPUs to scan their email inbox, search the web or avoid learning something is still ridiculous to me regardless.