Let’s see it first. And without omitting training/infrastructure costs at that. Until then my comment is still accurate.

its a private company, what exactly do you expect to 'see'?

Anthropic IPO's in less than 5 months and I guarantee you any company that officially is in the black will proudly shout it from the rooftops.

> Anthropic IPO's in less than 5 months

pure speculation. about as valuable as my linked wsj reporting i suppose. given thats the case, maybe you shouldnt claim so confidently that they are money incinerators.

“pure speculation” is a bit unfair.

Back to the point: No one is profitable yet. This is a statement of fact. And if you are going to lean on “they will be soon” then I can absolutely say they’re going to IPO soon.

Ease off the gas. We’re just discussing a tech company.

Does Anthropic really expect to double their income without also doubling their expenses?

I’ve been hearing that anthropic is on the verge of profitability for probably a year straight. Until all the companies agree to stop the training arms race I just don’t see how it’s in the cards

This is one of the things people miss. If they double their customers, of course they double their expenses. Unlike SW, the marginal cost here is still high

I mean, it's possible that with the new datacenter from SpaceX, they could onboard more users than it costs them to rent. That's fair. But I kind of doubt that.

One thing that really stinks to me is that various AI boosters have been claiming insane profit margins (40%, 50%, ...), yet apparently Anthropic stands to (possibly) make $500M profit on $11B in expenses, that's clearly nowhere near 50%. Not to mention that they're not making profit on inference now.

So where do people get this confidence to pull random numbers from?

There we go back to the original question: are subscriptions profitable, API pricing wildly profitable, and they just lose all that money on fixed costs like model training; or do they actually barely make money on inference?

That's why talking about the profitability of inference without accounting for model training is interesting, because that is the deciding factor in whether more customers would help getting them in the green

Without actual data I don't know. My gut feeling is that they overall lose money on subscriptions (and especially the free tier that accounts for 95% of all users). And make thin profit (~5%) on API pricing.

But it's just that. A gut feeling.

I don’t think it’s a gut feeling. It seems to be the consensus that subscriptions are still heavily subsidized

its well reported that inference margins on api pricing are 30-50%

No it's not. It's well speculated. Can you give a single source that says they have a 50% margin on inference?