[simonw]

"OpenAI generated $13.07 billion in revenue in 2025"

Considering just four years ago they were a research lab with hardly any revenue at all, and no corporate muscles for earning revenue, I think that is a very impressive number.

(Sure, they're losing a whole lot of money too. Same goes for almost every other hyper-growth company in the history of tech.)

[raincole]

> Same goes for almost every other hyper-growth company in the history of tech

Except it's not true. No one lost $38.5B in a year just to 'hyper-grow' or whatever it means. Uber accumulated ~$30B loss over a decade.

Edit: I read it wrong. The loss was mostly caused by one-time event[0]:

> Before OpenAI’s switch late last year to become a public benefit corporation, investors in the company received convertible interest rights rather than conventional equity. Under US accounting rules, those interests were treated as liabilities and periodically revalued as the company’s valuation increased.

It looks like that OpenAI is actually quite in line with other companies that lost money to grow.

[0]: https://www.ft.com/content/e15b0d7e-ff6b-4f16-ba7a-4068feddb...

[Retric]

Depreciating assets is one of several possibilities.

[Retric]

That argument supports any levels of losses, however I also think it’s rather misleading.

Growth means some inefficiencies, but their expenses are largely around commodities like electricity and data centers not a sudden army of salespeople. They also got 150M 11 years ago and 1 billion 7 year ago, they where quite large in 2022.

Basically you don’t get better at writing checks to your local utility which limits how much they can control costs.

[simonw]

> They also got 150M 11 years ago and 1 billion 7 year ago, they where quite large in 2022.

I had to look that up, you're talking about investment there, not earned revenue.

The 150M was their initial funding (actually 130M I think https://www.clay.com/dossier/openai-funding)

The 1B was from Microsoft in 2019: https://openai.com/index/microsoft-invests-in-and-partners-w...

In 2022 they only had 335 employees (according to various internet searches but I can't find an original source for that number.) I can't find credible numbers for revenue from the GPT-3 API, which did have some usage - GitHub Copilot started charging a subscription fee on June 21, 2022 - https://github.blog/changelog/2022-06-21-github-copilot-is-n... - and that was running on the OpenAI Codex model so presumably OpenAI had some revenue from that.

[Retric]

We don’t disagree with the underlying facts.

That said, in many ways 335 employees is the midpoint between 3 employees and 30,000 employees. The CEO can’t keep track of everyone’s names and what they’re doing, you need layers of management, HR, etc. It’s not really a simple exponential function but 335 to 336 is way more automated than going from 3 to 4.

[truncate]

> Sure, they're losing a whole lot of money too. Same goes for almost every other hyper-growth company in the history of tech

That doesn't mean anything. There are examples to make both ways. E.g. WeWork

[fragmede]

and WeWork is awesome example because it fell apart before IPO. It didn't even make it that far. On the other hand, for all of the shit talking that goes on online, SpaceX is up 49% from IPO price.

All of the shit that people said about SpaceX is still true. It's still up 49%. I'm sure it'll take a dump the next time anything bad happens, like a rocket explodes, but now that it's public, I'ma be watching all their rocket launches so I can buy if that happens and sell right after. I'm also going to be watching because going to space is fucking awesome but I can't buy a trip on that rocket yet and and no one's gonna pay me to watch it.

[freakynit]

If your losses scale with your growth, while at the same time your competitors are eating into your future user-base, how are you ever gonna become profitable? Only two ways comes to my mind: regulatory capture, and moving upwards into full software-development house.

[bxk76]

Or a utility :)

Look at how a utlity works, in setting price specifically, for things that are considered a public good. The story is not about how much profit or revenue they make. Its about how do you keep it afloat and expanding in the coming year. Thats it.

[bandrami]

Compute is both rivalrous and excludable so it can't be a public good in an economic sense

[dofm]

$867 million of that was Softbank. News the market has not taken well.

[jacobgold]

Annual revenue of $13 billion per year puts them on par with Apple's AirPods revenue, which places them in U.S. Fortune 500.

[bambax]

AI doesn't work like the rest of the tech industry. The cost of selling another license for a software program is approximately zero.

In the case of AI the marginal cost of the next token is not zero, and is in fact probably not going down much with volume, if at all.

So I'm not sure one can argue that scale will solve everything. It's very much like the old adage "we lose money on every sale, but make it up in volume".

No you don't.

[hackcasual]

It's wild to think how efficient Internet services were prior to AI. The most expensive thing would probably have been something like encoding video. Now you've a substantial portion of a rack dedicated to a user in the case of something like fable

[Ekaros]

Best analogue we have is probably video streaming. Or maybe more so live streaming. Unless subscription based and limited time events it seems those don't do well. Twitch has lost money for how long? And most smaller players seem propped up in other ways.

So if there is real cost involved things start to look lot worse and might not be overcome. OpenAI is unlikely to be exception for me.

[nl]

But video streaming can be very profitable! Youtube and Netflix are great examples.

[pqtyw]

But there is no indication they are losing money on tokens when R&D and other expenses are factored out? The margins on API are likely very high so the higher the volume the more likely they will be able to cover the other mostly fixed costs.

[bambax]

Maybe. We'll see.

Also, what are they calling "R&D" exactly? If it is training new models, which needs to be done almost constantly and means spending billions on energy and newer GPUs, then it's not really R&D, but rather operating costs.

[echelon]

Yeah, but they have no moat.

They gave up on video because three separate Chinese companies were kicking their ass (and for cheaper).

Google has a better image model in the majority of cases. Much faster, too.

Claude Opus and Fable are like a billion times better. It's not even funny. Codex can't do Rust at all.

What does that leave them? Ads in ChatGPT? I've started to just rely on Google search blended with Gemini answers now because it's faster and doesn't spit out a 20-page essay of useless effusive prose.

Open source models will eat them from the bottom.

Will those enterprise contracts be renewed in a market full of alternatives?

There's nothing sticky about this company.

They're making a necklace with Jony Ive though, I guess?

[chrisco255]

They still have the most recognized AI brand name and they are still the most popular LLM. For most users, a 10% diff between Claude and GPT isnt going to move the needle plus it seems to be a horse race anyways. I think their user base is stickier than you would think. Still, it isn't as sticky as social media and it is cheaper to switch AIs than email accounts.

[zozbot234]

Opus 4.8 is quite weak. And GPT-Pro is very much available unlike Fable, it's just not hooked up to the Codex harness yet.

[qwytw]

Will it be? It's so obscenely slow and expensive and its not obvious it could provide a lot of value for non highly specialized tasks.

[zozbot234]

So, just like Fable? You can shorten the thinking effort to tweak the "slow and expensive" part a little bit, but at the higher end being more meticulous than even Fable is actually a benefit.

[Razengan]

> Google has a better image model in the majority of cases.

Not always. A couple months ago (before ChatGPT Images 2) I tried various prompts on both Google's Nano Banana or whatever and ChatGPT.

"Capybara riding a tricycle. It has 7 tentacles instead of legs"

Google got the number of tentacles completely wrong: https://i.postimg.cc/nzY30y7X/Capybara-Gemini-Nano.png

and after some additions like spotted fur and multicolored tentacles, it was no contest:

ChatGPT: https://i.postimg.cc/02c2LrxV/Capybara-Chat-GPT-before-Image... (although there's still kinda 1 extra tentacle)

And Google still seems to have that odd choice of a European plaza/square/cobblestone street background for everything.

> Claude Opus and Fable are like a billion times better.

NOT at ALL: https://i.imgur.com/jYawPDY.png

Subscribed to Claude Opus for 2 months, with a few months gap between subscriptions to try different versions.

The UX/UI around Anthropic's products was excruciatingly annoying, right from the payment process, and Claude's AI was often hilariously dumb and "trying too hard", constantly full of "oops, you're right" backtracking and often borderline dangerous.

I tried Claude and ChatGPT Codex side by side on some tasks, with the same prompts. Each time, my confidence in Claude fell.

I've been subscribed to the $20 ChatGPT plan for more than 1 year, and this month, I am trying the $100 plan for 1 month.

ChatGPT Codex has been actually helpful and made me more productive enough that I can't imagine going back to coding without it.