OpenAI Losses Increased Nearly 8X in 2025, with Spending Hitting $34B

https://www.wheresyoured.at/exclusive-openai-financials/

by spking • 1 month ago

223 373 1 month ago

wheresyoured.at

rvz2• 1 month ago

They know it is a scam, but it doesn’t matter as it is now too late.

That ship has sailed long ago into the IPO sunset.

thereitgoes456• 1 month ago

That’s absurd. Why couldn’t it still fail, especially when their last raise was at 20x revenue or more? These numbers are horrendous.

watwut• 1 month ago

It can fail, but the cost will be pushed on small retail investors, pension funds, index funds etc. The investors and managers that made it fail and waste money will be rewarded and will remain rich. It will be the "socialize losses" situation.

muglug• 1 month ago

Revenue went from $3.7B to $13.07B — roughly 3.5x.

Operating loss went from ~$8.8B to ~$20.9B — roughly 2.4x.

Doesn't seem like a domesday scenario.

JumpCrisscross2• 1 month ago

Doesn't seem like a domesday scenario

Ceteris paribus, those figures imply a $45bn loss this year, $90bn loss next year and $110bn loss in 2028 before breakeven in 2029.

That's $250bn of losses to be financed from 2026 onwards. (They raised ~$120bn, $25bn up front and the rest based on milestones. So Another ~$125bn uncovered.) That only works if OpenAI stays a fundraising darling. So not a doomsday sceanario. But perilous, and dependent on short-term trends extending into long-term curves.

Schiendelman2• 1 month ago

You're adding absolute dollars rather than using percentages - that usually isn't how that works.

HlessClaudesman4• 1 month ago

This news matters because investors should prefer safer investments than: well at least it's not a "doomsday scenario" grade.

minimaxir2• 1 month ago

Tell that to the SpaceX investors.

pinkmuffinere2• 1 month ago

just for completeness, I think the closer analogue is probably total expenses: $12.48 billion to $34 billion -- roughly 2.7x. But this is still pretty close to what you said, so I don't particularly disagree with the numbers.

I do wonder if this comparison is really meaningful. It looks like if they can grow infinitely, then at some point they should be profitable. However, that's already a somewhat sad story ("in the limit as x->inf, we'll actually _make_ money!"). And there are of course limitations. Anthropic, Google, open models etc are all real competitors, and it seems to me that there will only be one winner. If openAI is losing money faster than the others, then it may not survive long enough to reach that eventual profitability. And finally, the human population is limited. There isn't a true infinity that the pattern can extend to. If we've only reached 10% of the TAM that's fine, but if we're at like 70% (which personally I suspect is about right), then this looks bad.

matusp• 1 month ago

The AI companies also have a lot of space to grow their income (more ads, price hikes, ...). It seems realistic for them to turn profitable. But the market expected much more from these companies.

lelanthran2• 1 month ago

The AI companies also have a lot of space to grow their income (more ads, price hikes, ...).

Ads, maybe, but not only are they already walking back recent price hikes, the paying customers were hitting the brakes even on the original price.

Note that this data you see (their increased revenue) came from a period where they were onboarding customers who were competing to see who used the most tokens.

IOW, this is the best-case scenario for them - customers with no cap on token spend.

But... the caps from customers came in before they hiked prices. Then they hiked prices. That resulted in a short-term boost to revenue to compensate for the caps. Now they are talking about walking back those hikes. That means they are going to find an equilibrium lower than their best-case scenario.

lelanthran2• 1 month ago

Revenue went from $3.7B to $13.07B — roughly 3.5x.
Operating loss went from ~$8.8B to ~$20.9B — roughly 2.4x.
Doesn't seem like a domesday scenario.

Those two lines are moving up and to the right, but are not parallel.

It all depends on where those two lines meet (the break-even point): too far in the future and the company will be dead anyway. Almost all companies will eventually be profitable; the problem is that the majority of them will need constant cash injections to keep the lights on.

Like the old aviation saying: even a brick will fly if it has enough thrust. doesn't make the brick a plane, though.

red-iron-pine2• 1 month ago

and again, there are good models racing right behind.

the brick has a lot of thrust but there is a airplane behind it, and it's moving on its own

thewebguyd3• 1 month ago

Compounding revenue & operating loss at those same rates (3.5x and 2.4x respectfully) puts those two lines meeting at around 2031. That'd be about 9-10 years to profitability, that seems pretty normal. Amazon took 9 years, Uber took 14 years before its first profitable year.

mikgp2• 1 month ago

I think it depends on a lot of things, not the least of wish is, this could be the worst their financials get, or depending how competitive this whole thing is, it could be the best:

https://www.reuters.com/technology/openai-considers-drastic-...

HlessClaudesman4• 1 month ago

“I had a guaranteed military sale with ED 209, renovation program, spare parts for twenty-five years… Who cares if it worked or not?!?”

pinkmuffinere2• 1 month ago

It's possible that I'm just not up to date with current news, but I'm having trouble connecting this quote to the article. Or really even understanding the quote at all. Can you elaborate?

HlessClaudesman4• 1 month ago

The commenter above seems to be describing late stage capitalism, where businesses exist mainly to milk investors, as told by bad boy tech executive Dick Jones in the 1980's action movie RoboCop.

red-iron-pine2• 1 month ago

dystopian robocop reference

nstart2• 1 month ago

I'm a little confused here. Cost of revenue is lower than revenue. That's good. R&D is the main contributor to losses here and this seems normal in an industry like this. For OpenAI specifically, I think this is problematic. They were the first movers but despite the large R&D they've lost so much ground to Anthropic despite Anthropic seemingly gifting them with weird PR self owns. But if we were to extrapolate this to the industry as a whole, this seems more positive than negative. Am I reading this incorrectly? Unless there's an assumption that R&D costs have to forever go up in order to increase revenue, I feel like this shows that the AI industry is actually on a path to profitability in the long term.

Whether it can physically be as all encompassing as it makes itself out to be or whether it will just be healthily profitable remains to be seen. Kind of like how Uber went from "We'll autonomously drive the world" to "Look, we deliver food, goods, and people to locations and we figured out how to do that in a way that makes profits. Also, ads".

Refreeze5224• 1 month ago

How in the world could you read that article and think there is anything positive about OpenAI's prospects? We've been hearing for months that these companies need to make trillions of dollars in a handful of years, growing at record rates in order to break even and justify their massive outlay.

It's not going to happen.

nstart2• 1 month ago

I tend not to focus on that future too much. I used to do so long ago. For example, how could Facebook possibly justify their losses while asking for such a big valuation? Same for Uber. Same for any number of big companies. And it turns out that growth in the future is impossible to predict accurately. Shopify is a good example where at the time the addressable market of online stores was tiny. But it turned out that Shopify created its own market which is huge today. Technology improvements have a way of creating new markets which far surpass today's total addressable market. Factor in currency depreciation and whatnot and sometimes, futures that looked impossible turn out to be possible.

Not saying anyone is wrong in pointing at the buildouts for AI and questioning its feasibility. Just making the argument for why I personally only look at operational costs and revenue because it's the only real-ish value I can look at and judge if a business can grow sustainably.

As a counter point, the red flag to all of this is R&D costs growing for each model release. If that continues and revenue cannot outstrip it, then these companies have a problem and it'll probably be that just 1-2 frontier labs can survive this once the dust settles.

grey-area• 1 month ago

Cost of revenue is lower than revenue. That's good. R&D is the main contributor to losses here

What is counted as R&D is completely arbitrary. These figures are just playing accounting games to attempt to hide the massive ongoing costs.

We’ll see a little better when they IPO and are forced to attempt to make money but I wouldn’t invest in this business.

Certhas2• 1 month ago

The Uber comparison makes no sense. This is the opposite situation. Uber lost money on rides, OpenAI is (possibly) making money on inference. Uber used an R+D moonshot to autonomous driving to justify capturing an established industry without reducing costs meaningfully. OpenAI has a core product that risks becoming a commodity with open source models only 6 months behind.

simianwords10• 1 month ago

Uber didn’t lose money on rides other than some edge cases. What’s your source for this claim?

JCW2001• 1 month ago

"Cost of revenue" isn't the entire cost of running the company, (ie R&D, operations, sales, marketing, etc). It's just a cost they've associated with revenue IN ADDITION to the other costs I mentioned.

HSBC say they need to turn a 13b revenue to 200b by 2030 AND also find another 204b, in order to become profitable.

thewebguyd3• 1 month ago

It's just a cost they've associated with revenue

Its a little less arbitrary than that. Cost of Revenue/Cost of Sales/Cost of Goods Sold are clear, if you're following GAAP. To label these expenses as cost of revenue, they must meet the matching principle in that the expenses must be directly tied to the generation of specific revenue. If you didn't make that "sale" then that specific cost would not exist.

Other operating expenses come later on the income statement.

Total Revenue - Cost of Revenue = Gross Profit first, then you subtract OpEx from there for EBIT.

For OpenAI, I'd assume cost of revenue is almost directly inference costs + customer support & app dev.

EmiDub• 1 month ago

Cost of revenue is lower than revenue.

I’m not sure how people are looking at numbers that show, even if we wipe off the enormous R&D expenditures, they are still in the red for inference + sales/marketing + admin and responding “this seems positive”.

It’s like being a sold a car and being told “well if you ignore the fact it has no engine it’s a good buy” yet it also has no wheels.

Unless there's an assumption that R&D costs have to forever go up in order to increase revenue, I feel like this shows that the AI industry is actually on a path to profitability in the long term.

There are three futures right, I’ll rank them in order of fantasy -

1. Someone achieves AGI. At that point the economics of an individual company don’t even matter.

2. R&D costs do have to forever continue, because LLMs can be continually iteratively improved. Much like chip development, there is no end in sight, at least not on a near term timescale. If you are not continually at the frontier, customers will use a competitor or open/local alternatives.

3. LLMs reach a plateau of functionality. Further gains are minimal, quality reaches the apex of what the technology permits. In this scenario the hyperscalers have no business because open/local models will rapidly reach that same plateau as well.

surgical_fire• 1 month ago

The leaked numbers completely ignore how much of their compute is subsidized.

It also ignores how much of "R&D" is actually needed for the thing they offer to keep working. Looking at the thread everyone seems to be presuming "R&D" is all "training new models", but that is uncertain.

raincole• 1 month ago

Revenue: $13.07 billion
Cost of Revenue: $7.5 billion

It's almost too good to be true. Did OpenAI intentionally leak this? It singlehanded eliminate the biggest concern: that tokens are sold at loss.

dofm3• 1 month ago

I think it does look like an intentional leak, but I disagree that it even shows with any clarity that inference is profitable.

minimaxir2• 1 month ago

At the end of his previous article (https://www.wheresyoured.at/ai-is-slowing-down/), Ed hyped this news as "a story that will possibly burst the AI bubble" and "imagine what the worst possible thing for me to get would be and you’re probably close." This news doesn't fit either criteria: OpenAI losing billions of dollars isn't shocking news and both AI boosters and AI skeptics have likely assumed that. If anything, the news that OpenAI has $25B on hand in cash as reported here, plus the $122B raised in March, show that OpenAI won't implode for another year or two if it does...and that doesn't say anything about the AI bubble. There's also the confounder that Codex wasn't released until this year which turbocharged revenue with an uncertain increase in operating costs, so it will be difficult to extrapolate 2025 finances to 2026 and beyond.

When I read "the worst possible thing for me to get" I had assumed it would be evidence that inference/Codex is fundamentally unprofitable (as Ed often blogs about) but there isn't enough information here to support that argument either: revenue is still greater than cost of revenue, and the major losses are clearly delineated.

besterman232• 1 month ago

Yeah, this pretty much seals it for me that Ed has basically nothing. Sure OpenAI isn’t currently profitable, but this doesn’t say to me that they can’t become so soon(ish).

thewebguyd3• 1 month ago

I had assumed it would be evidence that inference/Codex is fundamentally unprofitable (as Ed often blogs about)

I'm not sure where they'd get that idea from? If inference was fundamentally unprofitable, I don't think we'd have seen the massive CapEx spend & VC cash flooding into AI, it'd be a negative gross margin trap if that were the case.

It looks unprofitable because of the massive CapEx spend right now to build data centers.

People that think inference is not profitable are mistaking the total compute cost as inference cost, when really it needs separated into training compute vs. inference compute.

The bigger question is, is when does training slow down, if at all? If we hit plateaus with LLMs, at that point inference becomes nearly pure profit once you own the compute (and a hardware refresh cycle every 3-5 years).

LLMs eventually hitting a dead end for more advanced capabilities is what would spell trouble for the labs. Any existing hyperscaler cloud can run inference all day long, as long as they have access to a model. They don't need OpenAI or Anthropic for that. The frontier labs entire valuations rely purely on them staying ahead of the commodity curve. The moment they can't do that, they're done.

dgellow5• 1 month ago

I had assumed it would be evidence that inference/Codex is fundamentally unprofitable (as Ed often blogs about)

Ed's claim is that they haven't shown inference to be profitable. Which is true? And that he personally believe it is unprofitable (his personal opinion, not what his data report).

I think that's a meaningful distinction with your statement

manwithopinions• 1 month ago

I think Ed would argue that if 90% of your customers are only using your product because their usage is subsidised and the money to cover that subsidisation is coming from unsustainable customers tokenmaxxing then you are “fundamentally unprofitable”.

The question is, can OpenAI survive if customers start tokenminning? A pure inference business could be profitable but that’s not the business OpenAI are in. OpenAI has a billion users that OpenAI loses money on.

simianwords10• 1 month ago

What is the right way to deal with Ed Zitron articles because he’s historically extremely inaccurate and makes wild claims.

People ignore all his horrendous takes from last year and still eat this years “analyses” like it’s Gods words.

He has been predicting the doom for years and years now and it is strange to see HN still putting credence here.

This is what he said around a week back

“ One of my sources has come forward and brought me a story that will possibly burst the AI bubble. The reason they brought this to me is that I’ve shown — and will continue to show — that I actually give a shit about this industry and the people in it.

If you’re wondering what the story is, know that it’s the information I’ve wanted for years, delivered as I have always wanted it, and I will treat it with the reverence it deserves. Imagine what the worst possible thing for me to get would be and you’re probably close.

I expect it to be out in the next two weeks, and you’ll know exactly when it runs. There’ll be a podcast and a newsletter, and very likely follow-on coverage elsewhere.

I can guarantee you it’ll be worth it, and you’ll be stunned by what I report.”

This is qanon tier stuff. He’s been pulling this shtick for a while and people still haven’t caught on.

besterman232• 1 month ago

Yeah if this is his “information he wanted for years” it’s pretty abysmal in terms of crashing the “ai bubble”.

saberience• 1 month ago

Yeah he has zero credentials and authority and an agenda to push. Not to mention most of his articles are financially and technically illiterate and full of mistakes and inaccuracies.

No idea why his shit keeps getting submitted.

simianwords10• 1 month ago

I think there's some fundamental thing in his writing that speaks to people -- they want AI to fail and they want a prophet to give them reasons to think so.

dgellow5• 1 month ago

Genuine question, do you have examples of inaccuracies and mistakes? If you ignore his caustic tone and predictions what I’ve seen reported by Ed Zitron has been accurate.

NoGravitas2• 1 month ago

Ed Zitron is always prematurely correct, which is the worst kind of inaccurate (apparently).

lbrito3• 1 month ago

I don't think people ignore anything. Every single Ed Zitron post on HN has dozens of top-level comment exactly like yours, "No no no don't listen to Ed, he's a hack and AI is great".

sourcegrift• 1 month ago

Ed Zitron has proven trump wrong so many times it's going to be hilarious how right it will come out on this

Traster• 1 month ago

To be honest I almost think the numbers are irrelevant. In 2024/25 there was a lot going on - will AI replace authors, film makers etc. Will it replace social media (anyone remember Sora?). A tonne of that stuff didn't work out. At the tail end of 2025 a real product market fit emerged. Coding agents. They work. They do a job that you can actually profit from.

So everything else is kind of academic. Of course they were losing money in 2025, they had a technology that was kind of cool - clearly eventually going to deliver something great, but they didn't actually have anything somebody should pay for. Now they have a thing that people will pay for. So who cares what they lost in 2025?

So what's important today is - how competitive are they with Anthropic in delivering that product. How do the economics of companies using AI agents for coding work. That's all. I don't think there's really an argument about them losing money on inference any more.

efficax• 1 month ago

coding agents aren't enough to justify the amount of capital invested

dofm3• 1 month ago

My key realisation from playing with open weights models on my own laptop is that at least where text is concerned, the vast majority of what an average non-programmer consumer thinks AI does, my laptop can now do with the wifi disabled. And arguably where speech and audio is concerned, too.

There is, put simply, a huge, huge information gap about the uniqueness of these commercial services.

There's an open question about how open weights models will be funded when they can't be used in a war between these companies, but the reality is that the amount Apple is paying Google for the right to distill Gemini, for example, is strongly indicative of the total size of the consumer market. Because pretty soon everyone's phones will be doing what local models can do.

Global markets will ultimately learn that coding agents are, at a first approximation, the only source of revenue for this stuff over the medium term at least, and the value proposition for consumer AI in the long term (beyond being a feature of a phone) hasn't yet been invented, and any that might exist depend on micropayments architectures that don't exist.

danny_codes5• 1 month ago

The free fast-follow situation with open models seems to be a big "if" here. It's not particularly hard to set up OpenCode for your company and plug in one of the myriad inference providers running free models. All of these stacks are one release away from being a dramatically different value proposition, as proved by, well, Anthropic themselves.

I guess we'll see if people will pay a premium for Anthropic in ~6 months, 12 months, etc. If not, well, it's a race to commodity.

simianwords10• 1 month ago

Relevant: https://www.ft.com/content/e15b0d7e-ff6b-4f16-ba7a-4068feddb... this uses the same sources and answers more honestly and Ed Zitron doesn't touch on this.

As OpenAI’s worth rose, the increased value of those investor rights created a roughly $30bn charge, added the person. The charge is not expected to recur following the restructuring, they said.
Stripping out the charge and other non-cash expenses, such as stock-based compensation of staff and computing credits from Microsoft, OpenAI’s losses were $8bn, according to the person.

mfru• 1 month ago

it will be so satisfying to see them crash and burn

atl_tom• 1 month ago

I think something people are missing in the headlines. The actual losses were 60b with 17b removed from the bottom line figure. To quote a reddit post "removing $17.87 billion in costs via that “net loss attributable to noncontrolling members capital”"

themafia• 1 month ago

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.

dylan604• 1 month ago

It costs money to get influencers to set up kool-aid stands on their platforms.

iaaan• 1 month ago

I've seen physical billboards in the Portland, OR area for OpenAI, so I guess that accounts for at least part of it. Not really sure what kind of return they're getting on those but apparently they can just do whatever they want, even if they're losing money.

hedgehog• 1 month ago

I didn't look at the financials but the subscription product is heavily discounted relative to the API pricing and that difference could well be booked as a marketing expense. They also have a string of grant and similar initiatives (like $50M each) that could be marketing. There's a lot of stuff they could assign at least partially to marketing, and it sounds like they spend money pretty freely.

tomlockwood2• 1 month ago

I've seen lots of ads saying I should use chatgpt to plan a workout or give me recipes. Thats apparently the killer app for 95% of the population at this point.

henry2023• 1 month ago

Don’t forget changing the background of a picture. This alone can triple the GDP.

Mehdi2277• 1 month ago

That aligns pretty well with a past job. Those two areas were very popular user interests. Third one was cosmetics like skincare routine.

timacles3• 1 month ago

The irony being that the majority of the American population doesn’t work out or cook

ralph84• 1 month ago

They have a large and rapidly growing enterprise sales organization. If you want to sell to enterprises you need account executives, solutions engineers, forward deployed engineers, etc.

zerotolerance• 1 month ago

I cannot consume any content anywhere without being slapped in the face with an unending stream of OpenAI ads and paid plugs. I'd guess most of that money is going directly to Google and Facebook.

sunsunsunsun• 1 month ago

They need marketing because they have competition that essentially offers an identical product. Why should a consumer choose openai over anthropic or whatever else there is? The answer is not obvious.

Gigachad6• 1 month ago

OpenAI will make fully autonomous killing machines while Anthropic wont.

parliament32• 1 month ago

They are paying influencers to pretend they use LLMs, and discredit Chinese models: https://www.wired.com/story/super-pac-backed-by-openai-and-p...

sensanaty• 1 month ago

Half of the comments on this site at any given moment are from bots or shills shilling OpenAI and Anthropic. Now include Reddit, Twitter and everywhere else with a tech audience, paying for all that "organic" marketing doesn't come cheap.

fragmede4• 1 month ago

Wait, shit, really? How do I collect the money? Tweet at @Sama to collect, or...?

fuzzfactor• 1 month ago

It's so polarizing I can't imagine how that $5.7B is being spent.

In every way imaginable and then more, looks like beyond the imagination :)

I don't like these products. I have several negative opinions on them.

You're not alone, and the crowd seems to be building at the same time enthusiasts are proliferating too.

So much widespread negativity I would guess that's about what it's expected to cost to fully overcome resistance and objections. Which must be bigger than we think, they sure have more information than us.

Mistletoe• 1 month ago

Beginning to see why he needed seven trillion dollars.

pluc• 1 month ago

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?

cj2• 1 month ago

I’d easily pay multiple hundreds. Possibly a thousand a month.

If I were really forced to.

LLMs provide me about the same value as a car does.

malux85• 1 month ago

I would probably still pay if the cost doubled, but I would also look at competitors, offline solutions, etc

We have benchmarks on our domain and it does there are models that are 2x to 10x cheaper for a small drop in percentage points in accuracy

cammikebrown• 1 month ago

Paying a thousand a month for a car is also very stupid.

zormino• 1 month ago

Agreed. For personal use it's already easily worth $100 a month (to me personally). More probably. For work, it's entirely based on its financial impact for a given role, and for some people/companies it will be worth the cost even at $X thousand per month per seat.

gonzalohm• 1 month ago

That's crazy. Can you provide some examples?

cjbgkagh• 1 month ago

I’d pay thousands a month, if I had no cheaper choices, my productivity is now limited by the intelligence of AI, I’m basically a PM now.

timacles3• 1 month ago

What in the world are you working on?

nancyminusone2• 1 month ago

I've spent a grand total of $25 on AI ever, so apparently my answer is $25. But I'm not a big time software dev like the rest of you.

When I bought my last GPU, running AI models locally was a consideration though not the only one, and I have it set up but haven't used it much yet. I mostly use the free tiers of ChatGPT or Google to write the occasional script for me. I guess they're going to have to inject a truly unfathomable number of ads to get their money's worth.

I have a feeling my experience is closer to an average persons' than a dev, but it doesn't seem like they'll be able to monetize just from devs even if each one is spending thousands a month.

Mwntalhwalth2• 1 month ago

I'm not a coder but now work way faster than the coder I pay, stuff breaks but it's tenable and it's easier to get things to completion as the harnesses get better.

Don't give up just keep trying you can truly build personally life changing things. Don't look at it purely from a how do I sell this lense, just empower yourself with these tools while the getting is good

vb-84482• 1 month ago

For personal use not more than 30$/month.

For work, it depends, but if I have to spend more than a few hundreds bucks probably I'll start looking for alternatives (local models, Chinese providers, ecc)

PS: I'm in Italy, I guess in several parts of the world these figures are even smaller.

flux3125• 1 month ago

Max 60 bucks a month. More than that and I'd just move to local qwen 35b or some other cheaper model on openrouter.

bigstrat2003• 1 month ago

Zero. It provides no value to me.

dofm3• 1 month ago

I will do nothing to “support” AI. Either it has utility or it doesn’t. I feel no loyalty or duty to help make it work if it doesn’t.

Anyway: Zero, as of right now.

I fully expect to be able to run useful LLMs on a machine I can justify buying for other reasons. I already can on the secondhand kit I own, and I don’t expect the cost-benefit analysis of local LLMs to ever really get worse.

If I ever need to pay for it, it will likely be to shift some of the capacity into the cloud for either business or pragmatic personal reasons (so I can just carry an iPad etc.)

I fully intend my expenditure to be negligible. Because once one realises that outspending others is impossible, only spending minimisation makes sense.

I foresee it potentially making sense for me to move some mature tools off a local LLM to openrouter, maybe. But probably to the same or similar models.

binaryturtle• 1 month ago

Never paid a cent, never will pay a cent. I have my principles.

It may put me at a disadvantage when it comes to quickly slop something together? But so far the free-to-use chat bots do as well for my needs.

dgellow5• 1 month ago

I don’t and won’t support AI. For a while I paid 200€ a month and would have been happy to pay up to maybe 600€. However I don’t want to participate anymore in using such an anti-human technology and industry

protocolture• 1 month ago

I pay for good tools that I use.

I spend 30 - 60 bucks a year with Horizon Labs.

I spend 25 bucks a month on Cursor. Cursor replaced an OpenAI sub.

Both support hobby projects. If either cost increased I would spend some time testing local alternatives and probably drop them.

Horizon Labs especially, I know that they have been matched by open models and are mostly a convenience at this point.

c7b• 1 month ago

I make an important distinction between cloud services and local AI. My lifetime spending on cloud AI is probably less than $500, and I don't intend to spend any more. But I've already dropped $2.5k on new hardware for local inference, and could easily see myself spending more in the future. In fact, I'm regularly browsing for deals. I would also be open to paying for local models, if there was a way to make that compatible with fully open models.

AI is so important, I want to have it under my control. Even if I have to pay a penalty in terms of capabilities.

mewpmewp22• 1 month ago

It depends on how much time it saves me and how much I make per hour generally, right?

If AI allows me to cut my time to do something in half on average or allows me to do 2x more it would be worth it to pay up to what my monthly income was before assuming my income scaled with my output.

bob778• 1 month ago

assuming my income scaled with my output

The problem is that hasn’t been the case for 50 years

danny_codes5• 1 month ago

Well probably your income will decrease slightly as your field gets automated. So you'll output twice the much for the same effort and make a bit less money.

timacles3• 1 month ago

I don’t think there’s a single person out there that will ‘support’ AI

Maybe it’s just your phrasing but people will only pay for what works, no one is loony enough to support a trillion dollar industry out of the kindness of their heart or spirit of innovation

carlosjobim• 1 month ago

Businesses know exactly how much they make or save thanks to AI. Take your hourly wage and count how many hours you save, and you know what it's worth to you. People who use AI for real world tasks would probably mostly accept double or even triple.

cliche• 1 month ago

I'm not surprised

orphereus• 1 month ago

Suspicious lack of pro-AI comments here

rvz2• 1 month ago

You mean the lack of pro-Anthropic/OpenAI comments, who are gambling tokens at their casinos and won't admit that they are very expensive.

This is because people here are quietly realizing that they fell for the "token-maxxing" marketing drive which was complete BS for you to gamble more money on tokens as the big AI labs gave heavily subsidized token prices they cannot afford.

Jevon's paradox does not exist at those companies, but it certainly exists at the Chinese AI Labs at Deepseek, Alibaba, z.AI and Xiaomi.

operatingthetan• 1 month ago

This is because people here are quietly realizing that they fell for the "token-maxxing" marketing drive which was complete BS for you to gamble more money on tokens as the big AI labs gave heavily subsidized token prices they cannot afford.

Good callout. All these "trends" in AI were definitely from the AI companies themselves in order to push the sales of more tokens. What's after agent orchestration? Whatever it is, it will involve a big spend.

pydry• 1 month ago

their PR department is probably still trying to figure out what narrative the bots should follow for this one.

NoGravitas2• 1 month ago

Apparently the narrative the bots are following is that "this proves that inference is profitable!"

thraway38375• 1 month ago

It's the thing to do in HN comments. Downvote anything AI related and armchair diagnosing AI coding as psychosis. :/

Luckily, we've seen this before. Doom and gloom when smartphones came out. And then the same again when mobile development was preferred and there was an outcry from the web dev crowd and constant downvoting of phone apps.

jazz9k• 1 month ago

The last fad was crypto and web3. Once AI hit the scene, it's pretty much dead now.

yieldcrv• 1 month ago

I want to see the person who thought they were losing only hundreds of millions

holoduke• 1 month ago

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.

llmslave• 1 month ago

Leaked: OpenAI is a rapidly scaling startup, has economics similar to other startups

pooploop64• 1 month ago

If anything this is MORE evidence that the infinite money printer will be coming online any second now! Yep aaaaany second now... OH THERE IT- awww one of you guys wasn't praying hard enough.

vb-84482• 1 month ago

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.

LaurensBER• 1 month ago

6bn seems excessive but despite GPT 5.5 arguably being better than Claude I don't see a lot of adoption of Codex yet.

Some of my coworkers even use Sonnet (the default in Claude Code for the 20 USD subscription) and see no reason to change even though that model is definitely "outdated" compared to current SOTA.

dj_axl• 1 month ago

Marketing might help at some workplaces, presumably that are dedicated to Microsoft, for example our network blocks Claude (and DeepSeek) and is slowly rolling out Codex team by team. They should encourage Amazon/AWS to market for them.

ai_slop_hater2• 1 month ago

most people are behind the curve

smashed• 1 month ago

If these numbers are right, it's actually not that bad. Cut r&d costs and they are mostly profitable.

vjsrinivas• 1 month ago

Cut down on the one thing they need to keep themselves relevant in this space?

stogot• 1 month ago

Watch them flare out like a star… but there is lots of questions re the the return on RnD. Is it worth spending another order of magnitude for only marginal frontier gains?

deepsun• 1 month ago

I bet any FAANG spend is mostly R&D.

If it's not materials, not energy or taxes, not manufacturing, not licensing or rental fees, then I can only think of R&D.

windexh8er• 1 month ago

People keep overlooking the fact that costs for these providers scale along with customer acquisition. Most startups don't have that linear expense. Also, training costs are accelerating to get new models out faster. One doesn't simply "get rid of R&D" costs as a comment upstream mentioned. I can't actually imagine R&D goes down anytime soon unless you're willing to play third fiddle.

Unless these frontier providers feel some type of squeeze or constraint the Chinese are well positioned to leave the US bag holders of an NVidia bound system. And if anyone has to wonder how one provider for a critical piece of infrastructure will go, well...

matt-p• 1 month ago

Even if they keep the R&D costs, more efficient inference and 0 Marketing spend also gets you there. Inference is honestly super inefficient at this point, we can do far better than GPUs, push utilisation up, build more efficient datacentres.

darth_avocado2• 1 month ago

So you’re saying if you cut all the cost centers a company would only have profit centers? If you ignore all the losses you’ll only have profits?

fearmerchant• 1 month ago

It's more like once you figure out how to make a really good lamp then producing lots of lamps will be profitable. But the lamps are currently suboptimal so we'll be in the red until that time.

__alexs• 1 month ago

This is private equity 101 no?

Gigachad6• 1 month ago

If they cut down on R&D they will be no better than the open source models you can run at cost yourself.

4d4m• 1 month ago

While you cant discount 100% R&D they are close, agreed

cmiles8• 1 month ago

Yes if you ignore all the reasons why they’re horribly unprofitable, they’re profitable.

R&D costs are hurting profit side and while you can cut that one just becomes irrelevant overnight in this space if you do, hence the problem.

taneq2• 1 month ago

R&D costs are hurting profit

That’s quite the hot take, considering it’s literally an R&D company that got to where it is by doing R&D.

chartpath• 1 month ago

Not to mention they will need to research how to make their models faster and cheaper to run in order to fit some margin within what people are actually willing to pay.

bijowo1676• 1 month ago

OpenAI can easily cut R&D costs by replacing engineers with Claude Code

root-parent2• 1 month ago

I am having difficulty parsing this sentence ... :-)

fsuts3• 1 month ago

Numbers are probably not right as classifying everything aa r&d is going to the temptation

mjamesaustin• 1 month ago

Actually reduce R&D to ZERO and they are still losing money.

natas• 1 month ago

Napkin maths.

Alphabet: ~$4.5T value / ~$403B revenue ≈ 11× revenue

Microsoft: ~$2.9T value / ~$282B revenue ≈ 10× revenue

OpenAI: ~$850B value / ~$13B revenue ≈ 65× revenue

Can someone explains that logic?

joegibbs• 1 month ago

AI is growing much faster than the other components of MS and Alphabet's business, and OAI is 100% dedicated to AI while the other two only have small portions on AI

margalabargala2• 1 month ago

Let's say Company 1 has $1B revenue and has grown 5x in the last year, and 20x the last 2 years.. Let's say Company 2 has $1B revenue and that's the same as it was last year and the year before.

Should these companies be valued the same?

ignoramous3• 1 month ago

Should these companies be valued the same

By who? Public money is looking for dividends (profits) not growth?

TrackerFF• 1 month ago

SpaceX: ~$2.5T value / ~$18.7B revenue ≈ 133× revenue

djeastm• 1 month ago

Growth versus blue chip (do we even use that term anymore?)

mvkel3• 1 month ago

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."

trhway• 1 month ago

Yes, it is like a new era - the startups have huge direct revenue on real products instead of "users" which yet to be monetized.

And the network effect which ruled for the last 20 years seems to have relaxed its death grip just a bit (of course it is still there as having more customers using your tools and models provides more training data, etc., yet the current network effect doesn't seem to have that high exponential value like before)

root-parent2• 1 month ago

> Inference is _highly_ profitable.

Totally untrue.

cactusplant7374• 1 month ago

How much does 1 million tokens cost OpenAI?

mvkel3• 1 month ago

"Revenue: 13.07b; cost of revenue: 7.5b."

This includes running inference for ~1b free users.

What is untrue about this?

xienze• 1 month ago

My takeaway from this is that it's incredibly validating as a business model. Inference is _highly_ profitable.

The problem is you can't just separate training costs from inference costs. If OpenAI just didn't train a new model for the next five years, sure, they'd do OK. Assuming all those dirt cheap Chinese models nipping at their heels don't make up the gap while OpenAI is resting on their laurels.

Without being a frontier model (read: continuous, incredibly expensive training), they effectively don't have much to sell. So inference and training costs are intertwined to some extent.

mvkel3• 1 month ago

Gemini's existence disproves this

Panzer04• 1 month ago

Isn't this what all of the big companies that spend a lot on R&D and engineers promise?

And then the reality turns out not to be the case - you have to continuously spend on R&D to avoid getting your lunch eaten by someone else.

This isn't a social media network with lockin either. People can and will just switch to whatever whenever they feel like it. Maybe it becomes a defacto standard like google but if someone is much better than you, well...

jrm4• 1 month ago

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.

mrcwinn• 1 month ago

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.

fsuts3• 1 month ago

”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.

JimTheMan2• 1 month ago

None of the free models offer anything even remotely close to the output you can get on a relatively inexpensive model.

I think that AI is going to become just another utility people pay to stay relevant. Same as their internet, electricity or gas.

nemomarx• 1 month ago

Will they do it at utility / commodity prices though, or the inflated costs we see now?

9eLeven• 1 month ago

Sonnet 4.6 is free and works really well for coding for me from just pasting `tree` and `cat` output directly in the chat window on claude.ai

amanaplanacanal• 1 month ago

another utility people pay to stay relevant

I'm guessing that might be so in certain professions, but I would expect the employer to pay for that. For the rest of us, it seems unlikely. At least for me, I don't have a need of a device to generate text for me. And I bet most people are are in the same boat as me.

shimman2• 1 month ago

The free models are good enough for any work (very little) that benefits from LLMs.

dtnewman• 1 month ago

They won't try to. ChatGPT is already starting with ads, which is potentially far more profitable (as evidenced by the fact that the most profitable company of all time makes 90%+ of their revenue through ads).

Barrin92• 1 month ago

as evidenced by the fact that the most profitable company of all time makes 90%+ of their revenue through ads

the biggest reason for this is that the digital ad market is a duopoly (charitably a triopoly if you count Amazon in), if all of the LLM companies start to go into ads that's going to be a much more competitive market for ad buyers. It's not going to be so straight forward when both customers and merchants have ten different places to go.

Also not to forget that ChatGPT has zero moat, unlike social Facebook and Google.

whalesalad• 1 month ago

Crazy that they have 50 _million_ paying subscribers and are still losing money.

fsuts3• 1 month ago

Altman bough a podcast and that Ives company

They don’t care about making money at present

eranation3• 1 month ago

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.

542458• 1 month ago

I feel like I have a different $20 plan than everyone else. I have no problem hitting my 5 hour and weekly limits. Don’t get me wrong, it’s a great deal compared to API pricing, but it’s a far cry from “unlimited”.

uberduper• 1 month ago

I get about 20 minutes of work from my 5h limit with the $20 plan. It wouldn't bother me as much if codex would continue after the token bucket refills instead of waiting for me to show up and tell it to continue. I don't jump to the $100 plan because I would be in the exact same situation.

eranation3• 1 month ago

Interesting. I'm mostly using Claude, so perhaps I'm not nearing the limits, but I do use Codex (for coding and reviews occasionally) and use chatgpt for second opinion many times, including "pro" research. Never got to my limits. But again, not my main go to tool.

perching_aix• 1 month ago

de-facto unlimited (...) for $20 a month

Would love to hear some details on that one...

Or was that a typo and you meant the $200/mo plan instead maybe? That one I could believe, assuming no or frugal subagent use that is.

eranation3• 1 month ago

Copying my other reply.

Interesting. I'm mostly using Claude, so perhaps I'm not nearing the limits, but I do use Codex (for coding and reviews occasionally) and use chatgpt for second opinion many times, including "pro" research. Never got to my limits. But again, not my main go to tool.

Auracle• 1 month ago

I’ve hit the limit on Codex/ChatGPT one time on the $20 subscription since it came out, when I accidentally left the thinking limit on very high all day. I still could have resumed using it just 2 hours later.

atleastoptimal2• 1 month ago

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.

harimau777• 1 month ago

I think that the issue most people have is that the degree to which they would need to be profitable in order to pay back their debt is not realistic. It is unlikely that they would be able to get that large a portion of US GDP and if they did then there will likely be riots in the streets.

atleastoptimal2• 1 month ago

WHy would there be riots in the streets?

marcosdumay2• 1 month ago

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.

ignoramous3• 1 month ago

just a matter of finding 5 billion people willing to pay US prices

This is how you know ads are inevitable. YouTube is probably a good indicator of how BigLabs will operate for free users.

qntmfred2• 1 month ago

I'd be cool with that. YouTube premium is one of the best value subscriptions I have. Steering people toward paying instead of ads-by-default is a net good imo

mikgp2• 1 month ago

What is the mental model folks have that “just do ads” is easy, like only two companies have figured out how to make money from ads and I imagine they won’t take the competition lying down.

krupan• 1 month ago

My coworker is already seeing ads while using ChatGPT

marcosdumay2• 1 month ago

Yes, their numbers can even work out into a sustainable business with ads only.

They just have to become the world dominant LLM provider by a large margin, and become a high-value ad provider with world scale.

I mean... They just have to repeat a Google. That would make them sustainable and a reasonable value for the investment.

jmalicki• 1 month ago

The win for something like OpenAI isn't getting a ton of customers to pay $10-100/mo.

It's getting businesses to pay $2k/mo or more per professional employee, like a lot of Anthropic customers.

Anthropic is ahead of them there, but that is how they win.

rapind• 1 month ago

Anthropic is ahead of them there, but that is how they win.

Isn't Anthropic currently killing that market though? I've been hearing about a lot of businesses pulling back after having experienced the reality.

bizzletk• 1 month ago

Wouldn't the real story be to get government contracts? Those are more immune to public fickleness and market competition and usually have truly ludicrous margins.

If they're the only ones who ̶a̶r̶e̶ ̶w̶i̶l̶l̶i̶n̶g̶ ̶t̶o̶ ̶b̶e̶ ̶t̶h̶e̶ ̶e̶n̶g̶i̶n̶e̶ ̶f̶o̶r̶ ̶a̶u̶t̶o̶n̶o̶m̶o̶u̶s̶ ̶k̶i̶l̶l̶b̶o̶t̶s̶ can draw a reciprocation dingle-arm to reduce soinosoidal repleneration, then "I'm sure the government will buy it" [0]

[0] https://youtu.be/Ac7G7xOG2Ag?t=89

reducesuffering• 1 month ago

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.

apatheticonion• 1 month ago

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?

SpicyLemonZest2• 1 month ago

Even if you discount superhuman AI (which I would emphasize that frontier researchers do not discount and expect to see soon) think it’s still hard to have enough confidence that the ground is solid. Someone in 2024 trying to go down this route would have invested a lot of now-pointless effort into prompt engineering.

jaynate• 1 month ago

For clarity, inference is typically a COGS and therefore hits Gross Margin vs model training which would typically be in OpEx (where R&D lives) and would hit operating margin.

vlovich123• 1 month ago

I wonder if we are at a point where the focus can shift to improving the cost of inference.

There's always working on improving the cost of inference, but I don't think this is an area of R&D that will slow down. The reason is:

1. A better competitor model risks eating away at how much they can charge for inference (i.e. revenue) 2. Whoever unlocks AGI will unlock even more growth 3. Even when you unlock AGI, you'll want to throw gobs of money at it to improve itself and all sorts of things.

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?

You're pricing it wrong and looking at it wrong. First, the per token price doesn't consider that a smarter model can end up using fewer tokens overall to achieve a result. Secondly, if the difference is between failing to accomplish the task and accomplishing the task, suddenly that 50x can seem like a bargain.

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?

At this time, someone without SWE experience + <name AI model> vs someone good with SWE experience and <name another AI model> is a no-brainer. The AI model is an accelerant but the "no SWE experience" will be accelerated into a wall. Now maybe that doesn't matter for prototyping and certain other things, but anything in production the lack of experience will hurt them with things they won't even know about or even know how to look for it (e.g. slow, insecure, etc).

jurgenburgen• 1 month ago

Even when you unlock AGI

Massive assumption there.

bko• 1 month ago

Let's put it this way, how much is 5% productivity bump worth to you?

If you're in the US and you're making 100k a year, that's worth 5k or $416/m. So you can buy two of the most expensive plans on the frontier models.

This focus on cost optimization is insane. Just use the frontier models. Even a marginal bump is worth whatever the hell they're charging, at least for now.

bombcar• 1 month ago

The problem is it might be worth it to the company, but likely not to you - a 5% productivity bump likely results in $100k a year.

cwillu• 1 month ago

Companies aren't paying for tokens so that their employees can capture the gains.

bruce3434342• 1 month ago

Everyone else will be 5% more productive. Then no one is "more" productive. So everyone has a higher output, but the same wages and hours worked. There was only a gap when usable AI first came out, some contractors could do the same quantity of work in less time and enjoy time off or do more jobs. Now the gap has closed or is closing. And using AI now is more about not being less productive than peers who do use it.

rolls-reus• 1 month ago

large companies aren’t buying subscription plans. my org has a 2k per month token budget per person and starting to explore optimizations like automatic model routing.

shimman2• 1 month ago

There is no evidence that these tools provide a 5% bump, if anything they are providing a 20% liability (pulling random numbers is fun).

Also where is the evidence that the workers have ever benefited from productivity bumps? The only thing that happens is surplus gets captured by the owners while workers are forced to do more.

Bad deal all around.

free_bip• 1 month ago

You're saying this like I would see that 5k in my bank account. If I'm 5% more productive that probably wouldn't even make it into annual review, let alone pay.

lenerdenator• 1 month ago

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?

There's a non-negligible percentage of the industry who have a pseudo-religious belief in AGI, so I wouldn't be surprised if that was, in fact, the goal.

Who knows, maybe they'll stop once the money dries up.

egeozcan• 1 month ago

If a model comes and makes developer + Deepseek even a little more productive, from employers perspective, it'd still make sense to pay a lot of money for that.

Deepseek shines for personal usage because it's possible to use it however you want and whenever you want with no session/weekly limits stress because you use the API and it's priced very reasonably.

Gooblebrai• 1 month ago

Unless we are genuinely pushing to find AGI, at which point nothing matters

I think the third coming out Jesus Christ in closer than AGI. Seriously, I dread how much of Silicon Valley is wrapped in this narrative of AGI and Singularity.

How can all these "rationalists" fail to see that this is what religion looks like: Faith and promises of heaven and hell.

SpicyLemonZest2• 1 month ago

These "rationalists" understand that beliefs should be evaluated on whether they match what we observe, rather than preconceptions about which buckets certain ideas fall into. If the Southern Baptist Convention had announced a theological breakthrough in 2022 that lets them map out the precise calendar dates of the events in Revelations, and using this map they made a series of specific predictions that ended up coming true, it would be rational to start studying End Times Christianity in more detail and irrational to say that it's religious so you're not going to worry too much about it.

emodendroket2• 1 month ago

That's interesting on Deepseek. But I think as long as the models are still making noticeable gains with each iteration it's hard to say "good enough."

typ• 1 month ago

A thousand 90 IQ cannot do what a 145 IQ can do.

Similarly, some bosses might believe that they can hire 100 cheap, unmotivated SWEs to replace Linus Torvalds or Fabrice Bellard and achieve something slightly worse. But in certain areas, it doesn't work like that.

andrekandre• 1 month ago

i agree with this

on the other hand, the sad reality is many swe are working on dumb crud apps and the code-quality is already very low ime, and the jury is still out if ai tools can long term replace those; but what i have seen first-hand isnt super promising do far...

amluto• 1 month ago

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.

3eb7988a1663• 1 month ago

I am also curious what fraction of that revenue is government contracts. If they got say $N billion in government contracts, that is not going to have meaningful growth in the future.

lbrito3• 1 month ago

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.

aizk• 1 month ago

Sam didn't lie, they are in fact a non profit.

bharxhav• 1 month ago

You are an LLM dataset's worst nightmare. XD

jcgrillo5• 1 month ago

I do not think that means what you think it means

wxw• 1 month ago

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.

YeahThisIsMe• 1 month ago

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.

MaysonL• 1 month ago

Who needed leaks to know that?

romaniv• 1 month ago

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.

robocat• 1 month ago

SG&A

= SG&A stands for Selling, General, and Administrative expenses

CPLX• 1 month ago

These companies are clearly calling things that are R&D that aren't R&D.

If you're building a model that lasts a few months before it's no longer the most current one, and maybe a year before it's completely unusable by anybody, then that should just be COGS.

Doing that, however, would betray the real problem with this business model.

lokar3• 1 month ago

Calling it capex with an appropriate depreciation schedule is more appropriate.

Gigachad6• 1 month ago

They are also likely overestimating the useful lifespan of the hardware. They keep extending the number of years on the GPUs to make the accounting look better.

chrisgd• 1 month ago

This is the venture model now though. Spend until profitable. Uber did it. It seems OpenAI could do it as well given we seem to be in a 2 horse race for foundation models and having capital to get better pushes them further ahead.

Gemini is number 3 in this race

hadlock3• 1 month ago

Before Uber did it, Amazon had been doing it for almost two decades. It's nothing new. There is a difference between 1 billion and 20 billion in losses, though. Amazon in, I forget, 2014? Ran a profitable quarter with I think $1 in profits, simply to prove they were in control of their finances, and "we can stop any time we want". Sam gets a lot of shade, but he's been around the YC block once or twice, I suspect whatever risk they're taking on is at least somewhat measured.

lokar3• 1 month ago

Uber did not need this much money to cross the finish line, and faced less competition.

coherentpony• 1 month ago

Uber’s situation was different, though. The reason Uber were bleeding money is because they purposefully made all their rides cheap to undercut the taxi businesses. People used Uber because it was cheaper than renting a taxi.

Now you can’t really find taxis anywhere, even at airports it’s a lot more difficult than it used to be.

Once the taxi business was disrupted enough, Uber’s pricing skyrocketed and customers had basically no other options for competition on pricing.

OpenAI basically created a new market. There is no AI chatbot incumbent to disrupt and swallow.

sfifs• 1 month ago

The problem here is that open weight models are already good enough for a majority of process automation and intelligence tasks and that is where a good chunk of efficiency corporate dollars are. So there's an ever shrinking slice of inference that will hit the frontier models and inference is where the insane margins are. Now to be fair, Claude co-work and Claude code/Codex do seem magical today and these potentially will continue to be high margin/leverage plays. Frontier models are also likely to push towards decision making - so we'll have to see how it shakes out but the bottom end is already commoditized and it is getting bigger and bigger.

wg0• 1 month ago

Yeah insane that people think it'll be okay in the long run but wondering how much different the financial status of other such company would be? Not much I guess.

jcgrillo5• 1 month ago

I can't imagine there's a large variation in costs per token for inference and training costs between companies, and since they're all basically doing exactly the same thing, and competing on price... yeah.

joshuastuden6• 1 month ago

They're not really losing ground to Anthropic. 5.5 was a bit better than 4.8. Fable was good, and was a jump over 4.8, but only incremental over 5.5.

Anthropic is also likely losing money, right?

firesteelrain• 1 month ago

I never get throttled by Codex at $20/mo however Claude throttles faster at same rate. I like Claude’s output in terms of code however

anuramat• 1 month ago

huh, I felt like (gpt5.5 < opus4.8 << fable) in terms of code quality, and (g ~= o < f) in terms of pure pass rate; which one did you mean? curious about your typical workflow/tasks

I want to like gpt5.5 but it's like an evil genie: bugs are fixed, features are implemented, you are now a proud owner of a 2kloc file with a single function that makes you wish you had keybindings for horizontal scrolling

frankacter• 1 month ago

According to Wash they are operationally profitable

https://www.wsj.com/tech/ai/mind-blowing-growth-is-about-to-...

Some question it

https://www.wheresyoured.at/anthropics-profitability-swindle...

nojito• 1 month ago

You're over inflating the S which is expected to increase as now they are "going to market" G&A is within expectations.

Revenue is still growing faster than costs and gross margins have continued to improve.

The real question is when they can start spending less on R&D and still compete.

airstrike• 1 month ago

The real question is when they can start spending less on R&D and still compete.

As a company making SOTA models? Never.

anjel2• 1 month ago

Not here to entirely disagree its bonkers, but Tesla lost about 6b until 2022 when it got profitable and has since returned a healthy multiple of its prior losses as profits.

winfredJa• 1 month ago

Tesla didn't have any real competition until recently from chinese side. 2nd OpenAI is a software company unlike Tesla

y1n0• 1 month ago

Tesla's losses were always a small fraction of annual revenue. OpenAI loses multiples of annual revenue.

fnord77• 1 month ago

They're already losing ground to Anthropic even with this much R&D.

Do we know how bad/good misAnthropic is doing financially?

ViscountPenguin• 1 month ago

Petitioning the corrupt head of state to force Anthropic out of business seems to be part of the business model.

easygenes• 1 month ago

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.

ganelonhb• 1 month ago

People are gonna lose so much money on their upcoming IPO lol

tty456• 1 month ago

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.

thraway38375• 1 month ago

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.

We need to get away from this idea that in order for one thing to succeed, the other must fail. We also need to stop thinking in binary and accept that all these things (profitability, local models, powerful laptops, etc.) can all happily coexist.

layer83• 1 month ago

Buyers of consumer storage, RAM, and GPUs care. People affected by the data center buildouts care. Workers losing jobs due to underpriced tokens care. People on the receiving end of AI slop care.

thraway38375• 1 month ago

People aren't affected by PC component prices. The MacBook Neo was introduced and selling extraordinarily well for $500 during this component price crisis. 99% of the population isn't building their own PCs or smartphones.

joshuastuden6• 1 month ago

They haven't done humanity a favor at all. The innovation that these LLMs have produced has been small. A few fun math theorems where the answer was gleaned from a pattern in the training data. Great,.but it doesn't change the world one bit.

That latest drug for pancreatic cancer? Yeah, all human. After the trillions already spent, AI hasn't come up with any new medications, no new inventions to save lives... Nothing

thraway38375• 1 month ago

We're only a few years into it, and yet all generations of folks are using it for all kinds of things and getting joy out of it. That's positive impact. Even folks outside of tech are having fun with it. That is a positive change for humanity. Similar to Radio, TV, smartphones, internet, microwaves and PCs.

It's already being used in the medical field in many different ways, and I believe it will be able to fold new proteins to help make new drugs. It's coming.

maximinus_thrax• 1 month ago

The money they're burning is not yours or mine. They're institutional investor money. So, again, who cares?

This is not happening in a vacuum. A lot of index funds and retirement accounts have bought into AI and AI adjacent companies, many with stakes in OpenAI. If OpenAI keels over, even when private, it will affect a lot of americans. If they IPO, it's even worse.

thraway38375• 1 month ago

Index funds are based on a variety of tech stock. This whole "if they keel over" has been beaten to death ever since Tesla is surpassed Ford in market cap. And then Twitter was bought. No market crash. There will be some market corrections, but nothing be alarmed about.

dev1ycan• 1 month ago

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.

blini-kot• 1 month ago

what a surprise! who would have thought, right?

jcgrillo5• 1 month ago

I'm just here for Ed's victory lap.

strenholme• 1 month ago

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).

epsteingpt• 1 month ago

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.

akomtu• 1 month ago

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)

coldtea2• 1 month ago

Of course it does. They all do. Anybody who though otherwise wasn't paying attention.

OpenAI Losses Increased Nearly 8X in 2025, with Spending Hitting $34B

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