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points by scheme271 4 days ago | 0 comments
Are those statements audited or fact checked? Inference profitability is great but how much of that profit gets eaten up paying back training costs, R&D, and operating expenses.
[–] Gareth321 4 days ago
No, and it’s very rare for Chinese companies to allow independent audits. I would not trust DeepSeek financial disclosures. However from industry data we can see that inference is often profitable. It’s the training which is very expensive. Which is not a big problem for Chinese companies since to date much of their training is just distilling frontier models.
[–] snovv_crash 4 days ago
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.

[–] scheme271 3 days ago
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.
[–] mike_hearn 4 days ago
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.