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Their models and inference frameworks are open, you can run them yourselves to check how many tokens per day you can generate, and then validate that against their API prices.

Not sure how they can get more transparent than that.

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That's conflating different things. Unless you believe you can instantly saturate any amount of GPUs you bring online, 24/7, with paying customers from day one, then theoretical max throughputs on a stack isn't the same thing as revenue generated. Customer acquisition costs are real!

Even if you could acquire infinity custom on day one for zero cost, revenue isn't profit.

My point was really about profitability in general. The inference portion might be profitable but if training and operating costs are very large, then that can make the whole thing unprofitable. E.g. if it costs you $100B to train a good model but you make $0.00001 per inference token, you may not be able to hit breakeven for a very long time.

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