alt Hacker NewsLeaked financial docs show OpenAI is losing billions of dollars a year
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Of course it does. They all do. Anybody who though otherwise wasn't paying attention.
Seeing that R&D costs are the lion's share, I wonder if we are at a point where the focus can shift to improving the cost of inference.
Unless we are genuinely pushing to find AGI, at which point nothing matters, LLMs in their current form don't replace knowledge workers but are an effective force multiplier. How good is enough?
For instance, I pay about $1-2 a month for DeepSeek. It's not as sophisticated as Claude, but it still doubles my productivity as a SWE.
If Fable comes out and demands 50x the price of DeepSeek in order for Anthropic to make a profit on it, how much more productive would I be compared to my personal experience + DeepSeek? 3x? 50x?
Is it cost effective for a business to hire someone without SWE experience + Fable verses hiring someone with SWE experience and DeepSeek? When does R&D hit diminishing returns?
So... 50% operational costs and about $100 spent on sales for each paying customer.
If they manage to keep those customers for several years without more sales, that bit looks like a normal "high-touch" business.
They shouldn't look like a "high-touch" business, but their unitary numbers look way better than I expected. They just need to grow some 10 times to star making a profit... Maybe 100 to cover the opportunity cost of their capital.
It's just a matter of finding 5 billion people willing to pay US prices :)
But it is still better than I expected.
”The company reports over 900 million weekly active users of ChatGPT, though only about 50 million of those are paid subscribers.”
With so many free models available the ai companies are going to struggle to convert active free users to paid.
These numbers seem insufficiently detailed to really evaluate anything. They’re had $13bn in gross revenue in 2025, and they cost of that revenue was $7.5bn. Both are growing fast (we assume) and the ratio ought to stay roughly constant.
But: how are they calculating the cost of revenue? Do they have rapidly depreciating assets that are also needed to produce that revenue? (Starlink has this issue.) Will their cost per arithmetic operation for inference rise or fall? (Anthropic is paying xAI an absolutely insane amount to lease GPUs. They must be betting that they will not need to repeat that.) Is a large portion of the cost allocated to R&D actually being used to support their revenue?
I certainly believe that the cost of inference can be plenty low for them to make a profit, but a more granular breakdown would make it easier to evaluate.
A few things to note - the financial literacy here is... sometimes lacking? 1. Revenue GROWTH is 3.5x; Expense GROWTH -> Slightly less than 3x. There's a path to profitability 2. However, the COSTS probably assume a 5 (or longer) year depreciation on GPUs. If that assumption dies, the whole thing goes down.
If R&D costs don't go up - where does the moat come from? Cheaper players catch up with 'good enough' and will erode their revenue. Most of human tasks just don't require that much intelligence.
They're racing toward 'superintelligence' that recursively self-improves.
No indication we're anywhere close to reaching it.
Going to be an interesting year to say the least.
Discussed yesterday: https://news.ycombinator.com/item?id=48550465
Is this surprising to anyone? I thought that was a given. I'm getting de-facto unlimited use of a model more expensive than Opus 4.8 for $20 a month.
If these numbers are right, it's actually not that bad. Cut r&d costs and they are mostly profitable.
My takeaway from this is that it's incredibly validating as a business model. Inference is _highly_ profitable. Of course, like any company that has ever tried to grow at breakneck pace, you run at a loss until you "win."
Elon must be licking his chops right now, hoping that the "OpenAI problem" will just solve itself which bumps up X.ai as a competitor to Anthropic but under the guise and financial manipulation of all of SpaceX and it's subsidiaries to fool the public into thinking it is a long term player.
Almost 6 bln in sales in marketing? It looks an enormous amount given that they used to have the best models and used to give-aways tokens.
I'm really curious about something: how far will you go to support AI? Clearly they'll need to monetize things further, would you still use [whatever AI you are paying for] if the price was doubled? Tripled? Where would you stop and would you stop using AI altogether or would you look at competitors?
Good analysis. But who cares? It takes a long time for companies to figure out how to become profitable. And I honestly believe that OpenAI/Anthropic etc. have done humanity a huge favor. The money they're burning is not yours or mine. They're institutional investor money. So, again, who cares?
It will become profitable. Local models and local on-laptop inference will get good enough. This argument has been made for decades. It's not like everyone is walking around hosting email and photos on their personal machines. Sometimes it takes a large investment to make servers and clouds for this stuff possible.
I wonder how effective the marketing is (not much it seems).
I was watching a World Cup match last week and one of the TV ads during half time was something to the tune of ChatGPT being used by kids to improve their street soccer skills. This was Brazilian TV. Anyone even remotely familiar with Brazil would find this ad deeply, thoroughly out of touch. I can't think of a worse chatbot pitch than that.
This headline is not what I would read from this. The numbers are more favorable than the general tone of rumors, and point towards the expected shape of a fast-growing R&D heavy business.
AI is a huge bubble, just as dot-com was a huge bubble (I remember when people spent huge amounts of money to have key .com domains; as much as people paid for linux.com back then, the domain essentially went nowhere), and just as buying houses for too much money with loaned money was a huge bubble.
Just as with the two previous bubble, we’re seeing companies hemorrhaging huge amounts of money, and when the dust settles the market is going to crash big time like it did with the two previous bubbles.
Unlike previous bubbles, this bubble isn’t giving people high paying jobs until everything crashes (programmers with the dot-com bubble; construction people during the real estate bubble), but it very annoyingly is making memory and SSD storage cost far too much causing computers to cost about 150% as the cost two years ago before the AI bubble was in full force, forcing Apple to make a “MacBook Neo” model with the absolute minimum of ram and SSD storage space.
Like the dot-com bubble, we will have very few winners left (with dot-com, the big winners were Amazon and Google) but unlike the previous bubble, it’s incredible how political this particular bubble is (i.e. the controversy around Grok).
I'm just here for Ed's victory lap.
The scale of the numbers is exceptional, but the shape is pretty typical for a high-growth, scale startup with a big TAM where a winner can take most. And compute, supply constrained as it is for the foreseeable future, is absolutely a moat. I come away from this thinking OpenAI is actually in very good shape given that revenue is growing fast enough that break-even has a clear path without doing anything draconian.
We are watching an experiment: how high the Tower of Babel can stand of it's built with AI slop.
"According to the narrative story in Genesis 11, the city received the name "Babel" from the Hebrew verb bālal,[e] meaning to jumble or to confuse, after Yahweh distorted the common language of humankind.[11] According to Encyclopædia Britannica, this reflects word play due to the Hebrew terms for Babylon and "to confuse" having similar pronunciation.[7]" (Wikipedia)
This title is not how I'd actually interpret the results.
Glad to see more sane takes in the comments. All these articles on their current financials are missing the point.
OpenAI is doing pretty well.
Capital expenditure is required to deliver on 1) better models 2) better infra and 3) better products. Insane CapEx is required to do all the above + compete with Google, Meta, Microsoft, Apple, Anthropic, etc. etc. etc. who are all trying to do the same. These financials are sane, considering the scenario.
Beginning to see why he needed seven trillion dollars.
what a surprise! who would have thought, right?
I'm a simple guy and I don't understand the "sales and marketing" cost.
I don't like these products. I have several negative opinions on them. To the extent they work and there is a customer base what marketing could you /possibly/ be engaged in? Doesn't the product sort of market itself? Or another way is this a product that you can market to expand your MAUs?
It's so polarizing I can't imagine how that $5.7B is being spent.
[dupe] Discussion on source: https://news.ycombinator.com/item?id=48550465
Pardon my French, but yeah, no shit?
AI companies are black holes for money the way delivery companies are (or were, considering the money people are willing to pay these days).
Most of them will disappear alongside the money people have bet on them.
During the internet bubble collapse in the 00s quite some companies went bankrupt. But that's actually a good thing. It doesn't stop progress. It creates new opportunities and new baselines. Same will happen here. AI will not be less or gone or reduced to useless. It will become better , bigger and faster.
I want to see the person who thought they were losing only hundreds of millions
Yet another Ars article adding nothing to Ed Zitron's post 2 days ago and the corresponding Financial Times article.
"Exclusive: OpenAI Losses Increased Nearly 8X in 2025, With Spending Hitting $34 Billion" https://news.ycombinator.com/item?id=48550465 (188 points, 2 days ago, 108 comments)
https://www.wheresyoured.at/exclusive-openai-financials/
Please stop posting Ars. It's just blogspam, sad as that is. We need to let it go.
I'm not surprised
Who needed leaks to know that?
Ha, not a problem.
Look, for coding and a lot of other things, AI is awesome.
But the here's the killer. I have a dinky 16gb VRAM card, and that's kind of the sweet spot for the level of AI I actually want. I don't want it doing too much, I'd rather create slowly than have it one shot something that I have to then pore over later.
Feels like a company investing kazillions in, i don't know, air-conditioning or building wi-fi. Yes, it's going to be around, and also no one's gonna need THAT MUCH.
Everyone's financial literacy seems to evaporate when discussing AI companies. They assume that companies need to be profitable or they're a bubble waiting to burst.
The whole point of the company is that they are investing a huge amount of money upfront in order to make models that are better and better, and thus have a higher productivity multiplier.
They are very profitable on inference, they just know that the race to AGI requires a huge amount of investment, compute, getting the best researchers, etc.
People are gonna lose so much money on their upcoming IPO lol
Leaked: OpenAI is a rapidly scaling startup, has economics similar to other startups
Remember when Nvidia gave us HBM for the 1080 ti and then took it away because it was "too expensive for consumer products"? I remember.
I feel like the 1080 ti is like a prophet of the current crisis, these companies are buying $10k paperweights per user to MAYBE... LUCKILY... charge what... $200 a year? and that is for every 1/100 users.
this same 10k hardware will be outdated in a couple of years...
It just doesn't make financial sense, if you couldn't sell standalone GPUs that people PAID for with HBM in them, what makes you think that you can sell a POSSIBLE subscription utilizing a $10k+ GPU?
This is the most obvious bubble of all time.
Anyone remember how immensely incorrect most of HN commenters were on Uber's eventual profitability? For years we heard endless admonishment of Uber being an unsound business model. They made $10b in profit last year, $150b company at 18 P/E ratio. I would take the average HN opinion of business profitability with a grain of salt.
The fact that people here are looking at these numbers and saying "this is fine" is absolutely bonkers.
Basically, it's a company that's not sustainable for two separate reasons. The first one is that they have an extremely high overhead. SG&A of 55% is really bad. The seconds reason is that their R&D costs are truly astronomical. They could probably cut those costs to some extent, but they're not going to cut them to nothing. They're already losing ground to Anthropic even with this much R&D.
To put it differently, even if OpenAI cut its R&D and inference costs by half, they would still be leaking money like a sieve.