Comment by written-beyond
12 hours ago
Define profit? If by profit you mean covering compute costs then yes you're correct. If by profit you mean covering spent RnD budget and future RnD budget allocations then no, by no means are any of these AI companies running at a profit.
Also these third-party providers are running magnitude smaller models than what Anthropic and OpenAI's power users expect from them. Yes the average chat message isn't being routed to the 1+ Trillion param model but people running CC or Codex on Ultra probably are. Those are objectively more expensive.
I am citing out of my head here, but think deepseek’s inference engine with their models create around 30 dollars per hours while it costs around 4 dollars, there might be other costs but if you look at the demand, it will become very profitable. I don’t understand why people are pessimistic about the profitability (I don’t want them to be this successful either). BUT why would they care about profitability right now. They believe in AGI, so do the big money people. They get their investments. This train is not stopping and I believe their predictions are correct (IMO we should not debate about timescales apart from spreading urgency). And for the lowering of prices, it is possible because they just can and hooking people now into their systems will be 10x more profitable in the future. In addition to all the juicy training data they get with real world clients. They are scared the others win, they are not scared that they run out of money.
People are pessimistic about profitability because it's basic economics. Pricing power comes from advantage and nothing else. In particular it doesn't come from demand because in a well functioning market supply will rapidly increase to meet demand.
The little companies inferencing DeepSeek have no advantage over any other company doing the same thing. Therefore, their margins should look like any competitive industry. Farming, supermarkets, airlines are my go-to example. Usually margins in the 3% to 5% range. Profit margin average across all industry including very profitable ones like tech or oil is only 10%.
The companies offering inferencing and nothing else are relying on subsidies by the open weight model providers. If those companies all stopped releasing open weights tomorrow the offerings on OpenRouter would see rapid traffic declines as the knowledge in the weights became stale and as other companies that invested in proprietary R&D overtake them. So being profitable on inferencing open weights is a very short term play, and there's no reason to think it's a great business in the long run.
I got our pocket god ChatGPT to fact check this discussion. No lab is profitable, it is a moonshot to expect they'll ever recover the billions frontier labs have put in behind these DCs. I never understand this argument everyone tries to make, AI is too expensive -> It will get cheaper as they scale -> AI is too cheap and not sustainable -> No it's very profitable on API -> go back to 1.
I am not an AI denier, I use it and I find it very useful. That said I can disagree with the current economics of the industry and their business model.
Inference economics only work for those who build on top of the models lol. It should be said that Anthropic and OpenAI suck at product development too - claude for finance, Sora, OpenAI web browser - wtf?
Its difficult for people to accept this because many want the model producers to succeed badly.
SOrry folks...