Live data from Hacker News

Are OpenAI and Anthropic losing money on inference?

martinalderson.com

361–370 of 495 posts

Re: Are OpenAI and Anthropic losing money on inference?

#361

Earlier quoted context omitted.

No, the argument is that Uber was going to lose money hand over fist until all of the alternatives were starved to death, then raise prices infinitely.

Taxis sucked. Any disruptor who was willing to just... Tell people what the cost would be ahead of time without scamming them, and show up when they said they would, was going to win. Uber (and Lyft) didn't starve the alternatives: they were already severely malnourished. Also, they found a loophole to get around the medallion system in several cities, which taxi owners used in an incredibly anticompetitive fashion t…

Spoiler alert: in most of the world taxis are still there and at best Uber is just another app you can use to call them.

And lifetime profits for Uber are still at best break even which means that unless you timed the market perfectly, Uber probably lost you money as a shareholder.

Uber is just distorted in valuation by its presence in big US metro areas (which basically have no realistic transportation alternative).

Re: Are OpenAI and Anthropic losing money on inference?

#362
post #276

I've done the modeling on this a few times and I always get to a place where inference can run at 50%+ gross margins, depending mostly on GPU depreciation and how good the host is at optimizing utilization. The challenge for the margins is whether or not you consider model training costs as part of the calculation. If model training isn't capitalized + amortized, margins are great. If they are amortized and need to b…

> whether or not you consider model training costs as part of the calculation

Whether they flow through COGS/COR or elsewhere on the income statement, they've gotta be recognized. In which case, either you have low gross margins or low operating profit (low net income??). Right?

That said, I just can't conceive of a way that training costs are not hitting gross margins. Be it IFRS/GAAP etc., training is 1) directly attributable to the production of the service sold, 2) is not SG&A, financing, or abnormal cost, and thus 3) only makes sense to match to revenue.

Re: Are OpenAI and Anthropic losing money on inference?

#364

From https://www.theverge.com/command-line-newsletter/759897/sam-... , Sam Altman said: > “If we didn’t pay for training, we’d be a very profitable company.”

He also said he got scared when trying out GPT 5, thinking “What have we done?”.

He’s in the habit of lying, so it would be remiss to take his word for it.

Re: Are OpenAI and Anthropic losing money on inference?

#366

Earlier quoted context omitted.

This can be technically true without being actually true. IE OpenAI invests in Cursor/Windsurf/Startups that give away credits to users and make heavy use of inference API. Money flows back to OpenAI then OpenAI sends it back to those companies via credits/investment $. It's even more circular in this case because nvidia is also funding companies that generate significant inference. It'll be quite difficult to figure…

There a journalist ed zittron https://www.wheresyoured.at/ That is an openai skeptic. His research if correct says not only is openai unprofitable but it likely never will be. Can't be ,its various finance ratios make early uber, amazon ect look downright fiscally frugal. He is not a tech person for what that means to you.

Zitron is not a serious analyst.

https://bsky.app/profile/davidcrespo.bsky.social/post/3lxale...

https://bsky.app/profile/davidcrespo.bsky.social/post/3lo22k...

https://bsky.app/profile/davidcrespo.bsky.social/post/3lwhhz...

https://bsky.app/profile/davidcrespo.bsky.social/post/3lv2dx...

Re: Are OpenAI and Anthropic losing money on inference?

#368

Huh. I feel oddly skeptical about this article; I can't specifically argue the numbers, since I have no idea, but... there are some decent open source models; they're not state of the art, but if inference is this cheap then why aren't there multiple API providers offering models at dirt cheap prices? The only cheap-ass providers I've seen only run tiny models. Where's my cheap deepseek-R1? Surely if its this cheap,…

There are, I screenshotted DeepInfra in the article, but there are a lot more https://openrouter.ai/deepseek/deepseek-r1-0528

is that a quantized model or the full r1?

Re: Are OpenAI and Anthropic losing money on inference?

#369
post #335

Earlier quoted context omitted.

I suspect we've already reached the point with models at the GPT5 tier where the average person will no longer recognize improvements and this model can be slightly improved at slow intervals and indeed run for years. Meanwhile research grade models will still need to be trained at massive cost to improve performance on relatively short time scales.

Whenever someone has complained to me about issues they are having with ChatGPT on a particular question or type of question, the first thing I do is ask them what model they are using. So far, no one has ever known offhand what model they were using, nor were not aware there are more models! If you understand there are multiple models from multiple providers, some of those models are better at certain things than ot…

[deleted]

Re: Are OpenAI and Anthropic losing money on inference?

#370

Earlier quoted context omitted.

What do you think his strategy is? He has to make money at some point. I don’t buy the logic that he will “scam” his investors and run away at some point.

He makes money by convincing people to buy OpenAI stock. If OpenAI goes down tomorrow, he will be just fine. His incentive is to sell the stock, not actually build and run a profitable business. Look at Adam Neumann as an example of how to lose billions of investor dollars and still walk out of the ensuing crash with over a billion. https://en.wikipedia.org/wiki/Adam_Neumann His strategy is to sell OpenAI stock like…

Why not build a profitable business like Zucc, Bill gates, Jensen, Sergey etc? These people are way richer much more powerful.
Post reply on HN