[knuckleheads]

Shouldn't we know a better answer to these questions once Anthropic's IPO materials surface publicly? I understand, and maybe even expect, SpaceX's materials to be all over the place and skate on by any discussion of unit economics, but the nerds over at Anthropic might just be forthright enough to just tell us what their margin is on tokens as part of their IPO.

[rich_sasha]

To be honest, making sense of finances of fully public companies is often hard, because in practice, accounting is hard. How you account for depreciacion, cost, investment, fixed vs marginal costs is in practice fluid, companies have an incentive to make it look attractive, while also optimising for tax and shifting revenue around to narrowly beat analyst recommendations.

Here's a concrete example. Does some random AI company make operating profit on inference? I.e. if you only kept marginal costs, would you make a profit?

Well, depends what you account as your costs. If you're using hand-me-down hardware from previous generation's training, how much do you charge yourself internally for it? Maybe you show less, so investors take solace in profitable inference, even if you're losing money overall. How exactly are you accounting for electricity costs between training and inference? Is your army of SREs mostly servicing training new models (R&D expenditure) or inference (operating cost)?

This even has a name, and is called the "big bath" approach. If investors expect one part of your business to be a fiscal black hole, just shove all your costs there. They are accepting of it, and you make the rest of the business look better.

I'm not accusing AI companies of cooking the books, rather I'm trying to highlight you could see all the cash flows and still not know how much money is made or lost where.

[verdverm]

I saw some commentary that their free cash flow is misleading because it doesn't subtract the stock compensation they are paying to attract / keep top AI talent. Their point was also that deciphering financial statements is hard

[brainwad]

Why would it? Stock compensation doesn't affect cash flow, it just dilutes the shareholders.

[verdverm]

Except that's the thing, they do stock buybacks so they do not dilute existing shareholders or lower stock prices.

This is the video I watched that explained the shenanigans (from the guests' perspective, not illegal, obfuscated)

https://www.youtube.com/watch?v=YrJzjC4kKCY

[wqaatwt]

Yeah but that’s very standard and pretty much all pre-profit tech companies do something like that when/if they can

[verdverm]

sure, the guests say as much, their point is that it is hard to determine their real free cash flow. They estimate Meta is 80% lower and Alphabet is 2/3 lower. They give more details and quarterly perspectives

[steveBK123]

Well it probably doesn't help that Dario is going around on podcasts saying things like "frontier labs need $1T of revenue or they will go bankrupt" lol.

[jimbokun]

Dario’s company may be creating super intelligence that will kill us all in the near future, but at least he seems to be brutally honest about all of it.

[manapause]

The irony in AI triggering societal collapse due to gross economic malfeasance is just fun to think about.

If AI was around in the early 2000s Countrywide.ai would have been a thing.

[wongarsu]

Which is just a flashy way to say "we have low margins and lots of overhead".

Considering how much they spend on sales, marketing and R&D that doesn't sound that absurd

[steveBK123]

My point is that $1T of revenue is A LOT. Apple & Google each only did $400B revenue in 2025. Facebook did $200B. Think of how many decades it took the 3 to get there.

So depending on how literally we interpret Darios comment, OpenAI & Anthropic need to get to Apple+Google+Meta revenue numbers in like single digit years?