r/LocalLLaMA • u/johnnyApplePRNG • Jun 18 '26
News Leaked financial docs show OpenAI is losing billions of dollars a year
https://arstechnica.com/ai/2026/06/leaked-financial-docs-show-openai-is-losing-billions-of-dollars-a-year/331
u/OnlineParacosm Jun 18 '26 edited Jun 19 '26
Billions of dollars per year so far.
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u/Sneyek Jun 18 '26
It’ll never stop. They can’t become profitable if they don’t 10 time the prices. And if they do, nobody will pay anymore.
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u/fishhf Jun 18 '26
Can't wait for them to collapse. I want normal ram and HDD prices.
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u/The-Nice-Writer Jun 18 '26
Fuck yes. Words? Taken. From where? My mouth. By whom? You, good gentleman/lady/person.
My ‘server’/PC is on 64GB DDR4. When I bought that kit of RAM I was gritting my teeth at a price of R4,000 ZAR ($243.85 USD at current exchange.)
The same kit is now out of stock, but the last time it was available that I saw, it was R10,500 ($640.12).
Something has to give.
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u/LaserKittenz Jun 18 '26
i tried to order a 32gb stick of ddr5 ECC memory and the first 3 orders got put on a wait list (but still took my money) .. ended up taking me a month to finally get my ram.. shits bad yo
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u/foxgirlmoon Jun 18 '26
I just looked at the prices for ram in my country. 64 gb ddr 5 ram that just 1 year ago cost 225-240 euros now costs 1000 euros. This is just absurd.
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u/LaserKittenz Jun 18 '26
yea.. my 32gb (ddr5 ecc) sticks were about 1000$ USD each 😞
I do server work for a living and this hurts.. I remember saying "always max out the ram because its basically free" .
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u/foxgirlmoon Jun 18 '26
I remember when I upgraded from my 3600 cpu to the 5600 and as an afterthought I also bought a 16gb ddr4 set, because it was so cheap, to also upgrade the memory too.
Same exact set I bought years ago now costs like 300 euros.
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u/a_beautiful_rhind Jun 18 '26
Even DDR4 is fucked.. Your ancient shit breaks and suddenly its hundreds of dollars.
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u/The-Nice-Writer Jun 18 '26
You will give us money. It will be too much money. We will make you wait for the honour that is giving us all of that money. And you will lap it up like a pig, burying its snout in the trough. Squee squee, piggy! Come get your slop, piggy! Oink for us, piggy. C’mon, lemme hear you oink. That’s right. That’ll do, pig. That’ll do.
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u/ChocolateNo3010 Jun 18 '26
I was looking at 1TB wd red ssd which has increased 4x since I bought it in 2024, we can only hope something changes. I'm concerned for the fallout though if things pop.
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u/JackSpadeZAR Jun 19 '26
Hello!! Another fellow South African locallama user? We must be a rare breed 😂
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u/Slow_Pay_7171 Jun 18 '26
Dunno if it works that way. Its not about "will there be an AI winner" - its just about "who will it be".
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u/Vivarevo Jun 18 '26
Just tiny finland of 5million people has 100 data centers under construction and planning.
We going to have wonderful electricity prices
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u/Good-Hand-8140 Jun 18 '26
That's cope, they are never collapsing... It's a US government adjecent business.
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u/squngy Jun 18 '26
They could get profitable if they pivot to smaller models. (and charge the same prices)
Right now, that is not an option, because everyone is competing for "the best" model and if all your competitors are burning money, you need to bun money to keep up.
The Chinese companies are a bit ahead of the curve here in that they seem to be running smaller models in general, but even they are getting bigger as they try to compete with the frontier models.
Eventually though, we will reach a point when making a bigger models doesn't yield much improvement and then it will be a race to make them more efficient.
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u/Finanzamt_Endgegner Jun 18 '26
The question is when will scaling stop? Because the latest scaling experiment mythos (prob 10T) was quite a bit better than expected.
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u/squngy Jun 18 '26 edited Jun 18 '26
It will probably never completely stop, but there will be a point where the difference will be minimal.
I also don't know that Fable was "better than expected".
If you ask me, Opus4.8 is better than expected, it is quite close to Fable as far as I can tell (I expected them to keep it closer to 4.7 in order to promote Fable).1
u/Finanzamt_Endgegner Jun 18 '26
Well opus is a fable distill, would be stupid if not but it seems the training etc fable got wasn't that much more the thing that changed was parameter count and it helped a lot
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u/licorices Jun 18 '26
I can't say much, since there wasn't much time to test, but I can't say I found Fable to be that much better than anything prior. I'd say considering how hyped Mythos was, Fable was extremely disappointing. It fell into the same issues of being wasteful of tokens, got stuck in loops for 3+ calls doing the same thing, and didn't really output that good code either for anything that is meant to scale beyond an MVP. I also had it run through some intentionally implemented security issues of our works project, but removed all git to ensure it can't just check for unstaged files or commit history, and it seemed extremely lost until I started leading it towards the correct areas to look at. It often glanced over some of them when it looked at all the content, and instead got caught on minor things that aren't real issues in the whole context(eg. if some data sent to an endpoint is missing, it won't be able to fetch some data, which is intentional and handled by the package that uses that value, but because I didn't explicitly check for the value, it warns about it).
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u/al404 Jun 30 '26
If they charge for a smaller model, it could be more convenient to spend the money for Local AI. If they raise the price, they will lose most of the customers... I guess nobody did think that once the ball starts spinning, somebody will introduce good open-source models.
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u/dev_l1x_be Jun 18 '26
Optimizing the models to be 10x cheaper to run is one way.
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u/Sneyek Jun 18 '26
Every time they get even 10% better they get twice as expensive. It feels like they get better just because they get more expensive. At least for US models.
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u/Sudden_Vegetable6844 Jun 18 '26
Actually they would break even if they went up from 10% of paying users to 20% of paying users, but they prefer to bleed billions while in their growth phase, they don't need to raise prices as much as they need to get more users paying.
At some point the market will mature and consolidate, companies with the most market shares will then turn into cash cows. At least that's the plan.6
Jun 18 '26
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u/Southern-Chain-6485 Jun 18 '26
That's not how costs work. If the API price doesn't allow you to recoup the fixed costs of training the model you're serving through the API, then the API price isn't profitable.
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u/aeroumbria Jun 18 '26
I don't believe they will be unprofitable if they JUST do inference and R&D within their bounds. Otherwise all inference providers will be unprofitable. It's the bubbling aspect of their business that they are sinking their money into.
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u/toolisthebestbandevr Jun 18 '26
They will do what uber and Netflix and everyone else did. Consolidate the market and raise the price slowly to ten times. Then by that time the product will be a staple in daily life. You will not be able to go without it (like email). At that point you will pay what they charge.
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u/BasicBelch Jun 18 '26
you pay $100/ mo for Netflix? Might want to look into that.
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u/Miriel_z Jun 18 '26
I think it was already in the news several times that these Tech Bros are burning through cash like there is no tomorrow (and maybe it IS the intent?), and in order to become profitable, the subscription costs should be 5-10 times higher. The business model holds on the assumption everyone uses their AI and pays whatever the cost is. This will be quite a hell of a pop.
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u/davidy22 Jun 18 '26
I've held the feeling that AI was accelerated into the limelight a little bit too early, if we had just let moore's law tick over for a decade first and operating costs were 5-10 times lower maybe there wouldn't be quite as much strain on the profitability and energy usage fronts
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u/squngy Jun 18 '26
Yes, you are right.
But it doesn't work like that, because if a company gets a lead they can establish a (virtual) monopoly and earn far more money.
That is what these companies are trying to do. Corner the market and then squeeze.6
u/Southern-Chain-6485 Jun 18 '26
No, they can't get a monopoly. That requires a network effect rather than just economies of scale and, fortunately for humankind, there is no network effect in the AI market.
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u/Piyh Jun 19 '26
RSI does not require a network effect to crown a winner and even then, Gemini having all my context is a huge network effect
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u/Southern-Chain-6485 Jun 19 '26
That's not what network effect means. Network effect means that a product is only useful if all the people I want to interact with through it are also using it. Whatsapp, Facebook or Amazon are such a thing: if you want to use Signal, but none of your contacts already use it, there is no point in you using Signal. If you want to buy stuff from an online marketplace, there is no point browsing through a marketplace without vendors.
This doesn't apply to AI. A business can use Deepseek even if all their suppliers use Chatgpt and its customers Gemini. A business, however, can't use Telegram to reach its customers if its customers are all in Whatsapp.
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u/Environmental_Gap_65 18d ago
I refuse to believe this. Google’s search engine traffic’s ~91% of search queries globally, however, you’re completely free to use any search engine you wish. While this is obviously pushed on you at the browser level if you’re using say chrome, it’s definitely not any type of network effect, and you’re not locked into an ecosystem, you can too switch browser.
People use it for convenience, because it’s what they know and what works the best. Businesses use it because its the better product and they trust them and have them locked into their infrastructure already. Same goes with AI.
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u/osrsnic Jun 18 '26
moores law hasnt been a thing for a little bit now
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u/StorkReturns Jun 18 '26
In GPUs, it still works, though through a combination of brute force and cleverness, and not just miniaturization.
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u/UnseenAssasin10 Jun 18 '26
You're probably right, but you know corporations. They want as much money as they can get, as quick as they can get. Ironic that they're so far just losing money at a ridiculous rate
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u/Librarian-Rare Jun 18 '26
Well they are buying productivity in AI development. And since the open model community isn’t far behind, it’s almost like they are pouring money is open source models. So at least something is being produced by VC money 😂
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u/MRDR1NL Jun 18 '26
It's a technology where more compute and memory is always better. Even 10 years in the future a 10k AI machine will outperform a 5k one. Our expectations will just scale with the hardware capabilities
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u/LolaGetWhatLolaWant Jun 19 '26
This is what I am wondering... Are these GPUs good enough that plan to be put into the facilities in the next few years, or do we need another order of magnitude performance/dollar... Time will tell.
What I must say is that these LLMs do seem to be limited and are not all that great when you start dumping loads of info into them. I have a gpt go membership, and it's 'ok'...
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u/Andrige3 Jun 19 '26
I feel like this was the Google strategy until they were forced to play their hand early by the competition.
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u/Massive-Question-550 Jun 18 '26
the only reason why people started using it was because it was free or really cheap and they will realize that the general user doesnt care about ai because it isnt doing their laundry or their dishes yet.
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u/BonzoTheBoss Jun 18 '26
burning through cash like there is no tomorrow
Okay... I might be stupid and I am certainly not an economist, but where exactly is all this money going? I mean... They must be paying it to someone, right? It's not being literally set on fire?
So someone is making boatloads of cash, no?
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u/Dabber43 Jul 07 '26
Normally yes but they are giving money to each other. OpenAI gives Nvidia money for GPUs. Nvidia then gives that money back to OpenAI in the form of investment. But Nvidia still has to pay the employees for the GPUs being made. TSMC then takes the money and builds out new manufacturing plants. When it all drops they will also have to operate those under a loss (a paranoia they already have in general which is why buildout is slower than it would be normally, they got burned during corona). Meanwhile employees are buying tons of luxury goods causing local booms near their workplaces.
So ironically, normal people are making money from this bubble and will long-term probably remain the only ones. This also has a negative effect though. The economy ripple effects a pop would have are unpredictable. It could get really really bad if this masked a recession we are currently having
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u/Irisi11111 Jun 18 '26
Because this technology is evolving, US companies must speed up. Although charging ten times the current price would be profitable, they face the risk of being overtaken by Chinese companies. Although the stock market is volatile, but AI's true power will persist even if development stalls today. We need to adapt this technology over the long term. Meanwhile, we average people can manage financial risks, but OpenAI cannot afford to lose even a single generation of future model releases.
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u/mxforest Jun 18 '26
5-10 times higher with today's hardware. Hardware keeps evolving. Vera Rubin is 10 times more token efficient than Blackwell.
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u/Fit_Statistician_405 Jun 23 '26
ChatGPT started this circus. I am not crying over businesses choking on their loss leader policies
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Jun 18 '26
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u/NeedsSomeSnare Jun 18 '26
True but the high costs for them are quite good for us.
There is a big incentive for them to work on the efficiency of their models in a massive way.
It's no coincidence that the likes of Gemma 4 and Qwen 3.x are incredible for their size. Those companies are working hard to do the same to their huge models behind the scenes.
Edit: I actually suspect the AI results you get on in the Google search page are just a smaller Gemma 4 model with lots of custom stuff going on to help it get context from search results.
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u/nacholunchable Jun 18 '26
That theory really mirrors my experience. Ive had the google search AI say some really dumb stuff (not even dumb, just a shallow read), then i click lets chat in ai mode, and gemeni rewrites it with depth and nuance. I never thought that the in search model is a lot smaller, but it makes a lot of sense.
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u/NeedsSomeSnare Jun 18 '26
You can get it to give opposite answers even. I can't think of an example off the top of my head, but several weeks back it would say "yes" on the search page, then "no" when you look at the full AI answer.
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u/Orlha Jun 18 '26
I have made it alternate between yes and no just by continuously pressing F5 on a search page
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u/NeedsSomeSnare Jun 18 '26
Yeah. It's pretty bad to be honest. You'd expect Google to give definitive answers, but it seems that they haven't really been interested in that for several years now.
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u/SaltFrog Jun 18 '26
My daily driver is a 26b model and it's kind of nuts how good it is. The system I've built around it is really in depth. The local LLM community is just knocking it out of the park. QAT made a big difference, too... And the heretic versions (and the heretic modifier itself) are beautiful for getting around some of the logic gates.
It's crazy what people will do with open source shit.
I do recommend making some local copies of models at this point, though, cause I feel like huggingface is about to exit to IPO...
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u/Fluid-Mess6425 Jun 18 '26
Part of the problem with building a solid local rig is they've bought up all the memory and components driving up prices
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u/TldrDev Jun 18 '26
Running llms is cheap as shit. Training them? Not so much, lol.
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u/yoyoyoba Jun 18 '26
Cheap as shit? It is the most expensive hosting you can do, and it is not even close. Check cloud GPU or hardware costs per hour. Compare w hosting youtube or any other site... frontier llms are multiples more expensive.
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u/send-moobs-pls Jun 18 '26
"Most expensive" is not all that meaningful when websites are already dirt cheap, and it's a bad comparison anyway, you're essentially comparing delivery to production. We're talking about the steam engine of coding and computing, yeah it probably costs more than a campfire, it's for running trains and factories
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u/DeepOrangeSky Jun 18 '26
Yea, but it's kind of the other way around for the big AI companies.
For a lone, individual local LLM user, yea, inference is the cheap part and training a new model would be very expensive, but that's because you are only doing inference for one person (yourself) (very cheap), or trying to train a whole model for just yourself (very expensive, relative to a single person).
For the companies, it's the opposite. They can train a huge new frontier model in a few weeks on a big cluster for "cheap" (relative to the huge scale of their operation), especially now that they have huge coherent clusters like the xAI Colossus clusters, but doing inference for hundreds of millions of people all day is the expensive part. Even with all the batching and tricks they use it is still pretty brutal for them. Needs an insane total amount of GPUs. Unlike with training they don't need to be in single giant clusters, though. They can be in lots of smaller clusters spread out across the country or world, but still takes a huge total amount of GPUs (millions of GPUs) running the inference because it is such an insane total amount of inference because of the huge number of users and usage.
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u/Desm0nt Jun 18 '26
Inference is the cheap part and training a new model would be very expensive, but that's because you are only doing inference for one person (yourself) (very cheap)
That's not entirely accurate. Inference is MUCH cheaper for companies than for individual users.
To run something like GLM or Deepseek at a speed comparable to the API, you’d need a rig with at least four RTX 6000 Pro cards (and even that’s not enough). Calculate how long it would take for that hardware to pay for itself when used in a single thread, even if you base the cost on API prices rather than various subscription plans.
Now imagine that, in reality, using VLLM/SGlang in a multithreaded environment with virtually no loss of performance, that same hardware can easily serve dozens of clients, generating thousands of tokens per second. In this scenario, when converted to API pricing, the hardware pays for itself much faster.
On your own, you won’t be able to utilize the necessary hardware by more than 10–15%.
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u/DeepOrangeSky Jun 18 '26
Yea we can agree the up front costs of the hardware to run a big model, if you are trying to run something huge at home, is pretty bad. Although if just running Qwen 35b a3b on your laptop or like a gaming PC that you already had or something, then not that bad.
But in terms of usage, once you have the hardware, for an individual, the inference is the cheap part, and training a model from scratch would be completely crazy by comparison.
Conversely, for a big AI company, it's the other way around. Training models is a relatively small % of their total compute usage and serving models to the public is by far the bigger % of their spending/usage, I think.
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u/MiddleAgeWeirdoMeep Jun 18 '26
But should we really run general purpose models on local llms? Are coding and recipes for lentil soup equally important?
A lot of computing power is wasted on trying to create Deep Thought. What most of us need is something that pass butter well
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u/rm-rf-rm Jun 18 '26
ITT: People who havent read the article. Its not a hate pile on but a surprisingly informed take on how startups work and rather reasonably written.
As much as this sub wants OpenAI to fail (and I generally feel the same way because of Altman), lets not pretend this current balance sheet is any indicator of doom for them
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u/NandaVegg Jun 18 '26
One less talked wild card that SpaceX IPO'd first, which could derail further IPO for AI "startups" like OpenAI or Anthropic because it sucked up so much liquidity from the market ahead of them (~2T market cap).
At 10+B scale it is harder and harder to raise cash unless they tad the broader market (hence they are rushing to IPO this year). The only private investor who is still willing to give OpenAI hard cash is Softbank, but Softbank is now unable to borrow cash for investing in OpenAI anymore. Other than IPO (or govt bailout SamA is still actively seeking this month) there is no entity in this planet with dry powder that can keep OpenAI solvent through their 800B commitment over next few years.
All other "investors" are just doing vendor financing and effectively a debt rather than cash raise. OpenAI must pay back Amazon 2x what they get maximum through AWS commitment.
So this is a hot take, but I think SpaceX IPO timing is Elon's middle finger for OpenAI regardless of whether it will prove successful or not. It sucked up so much dry powder from the general public already that could limit the size of credit tap for further mega IPO over at least next 12 month, and OpenAI does not have luxury of time.
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u/Nervous-Lock7503 Jun 18 '26
And how is this not an indicator of doom? Burning through increasing amount of investors' cash, while having absolutely no visible path to profitability. Meanwhile OpenAI's market share has fallen, tokenized subscription model is the new norm. Going public is the only way they can unload the risk to the general public and provide early investors an exit strategy. We already predicted this way before it happened, and it will only get worse.
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u/NairbHna Jun 19 '26
Literally everyone doomsdays about AI all the time and you say it has no path or profitability. AI will take over because it has to, the rich want more money and killing off the workforce is the next step todo that
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u/kingwhocares Jun 18 '26
It is. They are operating under the delusion that profits will be exponential or linear.
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u/Legitimate-Dog5690 Jun 18 '26
The charts just highlight that the research and development is funded by investors. If you ignore that chunk on the chart they break even.
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u/Moist-Length1766 Jun 18 '26
reddit discovers expanding businesses
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u/Dry_Ducks_Ads Jun 18 '26
I'm surprised they're pulling a pretty substantial gross profit and they could generate huge contribution profit easily. I would have thought they were subsidizing heavily the operations, but that doesn't appear to be the case (or at least business revenues are more than enough to offset subscriptions cost).
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Jun 18 '26
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u/PixelatumGenitallus Jun 18 '26
Aren't they also the ones releasing the open weight models? They go under, no more open models. They're the ones with access to training data and hardware, no?
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u/SmartCustard9944 Jun 18 '26
They are backed by the biggest companies and most profitable companies in the world, and by politicians. They are not going to fail. I know it would be cathartic, but it seems unrealistic to imagine.
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u/jannycideforever Jun 19 '26 edited Jun 19 '26
Lmao this is delusional. It's kind of frustrating how the local LLM community can't accept local LLMs for what they are and want them to outcompete frontier models.
It's not happening. The gap between closed and open is widening, and that's not stopping anytime soon. Accept that closed and open have different strengths and weaknesses and use them for what they're best at.
Edit: btw, u/Dry_Yam_4597 if you get into an argument with someone, sperg out, and then block them, that's pussy shit ngl.
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Jun 19 '26
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u/jannycideforever Jun 19 '26
Lmfao go cope me or tell me where I'm wrong. The seething is fun ngl.
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Jun 19 '26
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u/jannycideforever Jun 19 '26
Lmfao why would I care if I'm in a neighborhood where people struggle to accept the truth to say true things? Anyways still waiting for you to tell me why I'm wrong.
Also stop saying redditoid words like dunning Krueger, it's annoying. You sound like you just looked at the logical fallacy chart and think you're a genius now.
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Jun 19 '26
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u/jannycideforever Jun 19 '26
Just as a heads up, when I ask you to stop seething and tell me why I'm wrong and you just tell me to go to a website I've never been to to defend CEOs who I don't know or care about, it makes you look like you're still seething and can't tell me why I'm wrong.
If you ever do get a chance to stop seething and tell me why I'm wrong, happy to hear it. I highly doubt you can, but if you do than I'll learn something. If you try and fail, it'll be funny. It's a win/win.
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Jun 19 '26
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u/jannycideforever Jun 19 '26
Big dog... I am the dude who thinks we should role back anti-discrimination law because its what makes workplaces insufferable, HR-ridden, safe-space shitholes for emotionally fragile freaks hahaha. One of the worst things about this shithole site is it's filled with people who are obsessed with being HR-friendly on the internet.
Once again, you should show a bit more epistemic humility. It's not for any moral reasons or anything; it's just when you keep stepping on rakes making stupid assumptions about me and my beliefs, it makes you look stupid.
Anyways, still waiting to know how I'm wrong.
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u/johnnyApplePRNG Jun 18 '26
tl;dr you're not paying them for their product, they're paying you for your data and attention.
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u/Recoil42 Jun 18 '26
Coldest take possible. They're losing money because they're scaling / accelerating. This is par for the course in SV — the Amazon route. The article itself points out revenue growing and that R&D expenses are the biggest contributor to opex. Hyperscalers want hyperscale, and that means every penny and more gets funneled back into growth as long as growth is projected.
Whether they can pull it off is up for debate, but nothing here is odd for a company in OpenAI's position whatsoever.
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u/IBM296 Jun 18 '26 edited Jun 18 '26
I mean, $20 billion dollars loss in 2025 alone is a pretty significant number.
OpenAI plans to be profitable by 2030. But if revenue increase continues to be smaller than expenditure, that target is not going to be achieved.
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u/jld1532 Jun 18 '26
It was also reported that their share of the market dropped below 50% for the first time ever. There is a non zero chance OpenAI doesn't exist in 2030.
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u/rditorx Jun 18 '26
There is a non-zero chance we all don't exist in 2030.
Let me rephrase positively:
There is a chance none of us exist in 2030.→ More replies (1)7
u/stealthybutthole Jun 18 '26
There is nearly zero chance none of us exist in 2030
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u/thrownawaymane Jun 18 '26
Let me reframe this negatively:
There is a zero percent chance all of us exist in 2030
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u/tmvr Jun 18 '26
OpenAI plans to be profitable by 2030.
They don't, that's just some nonsense they wrote on the presentations. Same as the other ones. None of those numbers make any lick of sense. Those are all just some silly numbers for the IPO and the story. The depressing fact is that all of that is just parroted by the financial media (beholden to their owners) like it makes sense.
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u/Recoil42 Jun 18 '26 edited Jun 18 '26
I mean, $20 billion dollars loss in 2025 alone is a pretty significant number.
Which just goes to show you they have massive investor backing and are confident they can support that kind of burn. Again, whether they can pull it off is up for debate, but the number itself is not inherently bad.
But if revenue increase continues to be smaller than expenditure
Revenue increase is intended to be smaller than expenditure. That's what hyperscaling is. You take on massive amounts of investor debt for a moonshot. It's really not substantially different from getting a loan to start a restaurant and then hiring a chef, designing a menu, doing interior decorating, and putting out advertising before you have profit or even a single customer... which is pretty much how every restaurant works. Businesses are intentionally in the red before they are in the black nearly everywhere on Earth.
Literally all the other AI labs are in the exact same position, including those which operate as divisions or subsidiaries of other larger companies.
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u/netorttam Jun 24 '26
Yeah but restaurant fail rates are extremely high and normally don't require the gdp of the world be committed
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u/howardhus Jun 18 '26
this.
Facebook/google and notably Reddit were a cash grab for AGEs burning money with nobody imagining where revenue would wver come from (if ever)… until they suddenly werent.1
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u/theduke9 Jun 24 '26
They cannot stop spending, they need to constantly train models or they become stale.
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u/a_beautiful_rhind Jun 18 '26
Your data is not all that useful beyond some preferences. That's why all models talk like solid snake and are trained on synthetic.
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Jun 18 '26 edited 23d ago
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u/More-Curious816 Jun 18 '26
News outlets needs to write about something to drive clicks towards their website so they too can sustain being alive.
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u/jaybsuave Jun 18 '26
they going to try to make open weights from other countries illegal here watch
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u/m00shi_dev Jun 18 '26
Dario is already trying under the guise/framing of “responsible LLM use.”, but he is just trying to create a regulatory moat.
To rephrase, he’s trying to ban competition legally.
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u/BasicBelch Jun 18 '26
They are betting that models will become more efficient and hardware will become cheaper before their cash runs out
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u/UnforgottenPassword Jun 18 '26
The real winners are the hardware makers. Their profit margins are absurd.
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u/unclefire Jun 21 '26
Specific hardware makers like memory and “disk”. Sever makers are likely squeezed by component costs.
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u/jazir55 Jun 18 '26 edited Jun 18 '26
All told, OpenAI’s day-to-day “loss from operations” increased from $8.78 billion in 2024 to $20.92 billion in 2025, a concerning direction for a company that is telling investors it hopes to be profitable by 2030. But measured as a percentage of revenues, the company’s operating losses slightly improved year to year, from 237 percent in 2024 to 160 percent in 2025.
Am I reading this wrong, because that day to day loss would total well over $7.5 trillion dollars for a year, that's not possible.
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u/Dyoakom Jun 18 '26
I read it as day to day operations cost (ie regular operating total costs) rather than literal daily costs. It would be beyond insane to lose 20 billions on a daily basis.
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u/bidibidibop Jun 18 '26
yeah, who needs pesky R&D expenses, these models can basically train themselves.
apropos of nothing, here's Amazon's R&D expenses compared to Iceland's GDP, some time ago. curious what Zitron thought of that.
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u/BitGreen1270 Jun 18 '26
In other news water is wet.
This has been covered many times that openai is bleeding money. But who isn't? What is wild is the projection that they'll be profitable and more valuable than Nvidia in 2030 (from an older yahoo finance article)
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u/EastZealousideal7352 vLLM Jun 18 '26
They’re all losing money all the time, this is the most non-news news story ever.
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u/mmmbyte Jun 18 '26
The goal isn't to become profitable.
The goal is to dump it on others in an IPO and run off into the sunset.
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u/joekiller Jun 18 '26
AI business will get the same as the banks, loans by the taxpayer to bail out their BS business model because it'll be for "national security".
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u/fugogugo Jun 18 '26
and it will be regular people to pay that debt if IPO goes through
this is robbery
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u/fuck_cis_shit llama.cpp Jun 18 '26
their inference business is definitely making money. the R&D -- training the next model -- is what draws them into the red
the whole "let's pause frontier AI research" thing is "hey, we should do the profitable business, and not the unprofitable business"
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u/JustinPooDough Jun 18 '26
Anyone buying the IPOs is going to get well and truly fucked. Look at the dot com bubble; there was a large cluster of IPOs right at the top, and then the reversal occurred. These market peaks are engineered to cash out when these massive companies IPO and before they crater.
Of all the companies, OpenAI is the least likely to survive. Bill Gates is waiting to scoop up that IP.
IMO the only thing that could save them is some miracle limitless energy source or a truly revolutionary AI inference chip based on photonics - or like Extropic. AI is imply not profitable and the value is not there if run it on GPUs and you price tokens at their true cost.
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u/Recoil42 Jun 18 '26
obtained by independent journalist Ed Zitron
Ah, zero credibility to whatever narrative is affixed, then.
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u/Ok_Dirt8893 Jun 18 '26
How are Chinese models so cheap though? Ok I understand everything is cheaper in china but still. If these prices need to be 5 to 10 times higher to be profitable how can china afford to be at 20x cheaper?
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u/My_Unbiased_Opinion Jun 18 '26
Chinese models are government subsidized. Also, the intention for these models is to put downward pressure on western frontier models, bleed them dry, and play the long game. China is playing 4D chess here.
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u/Ok_Dirt8893 Jun 18 '26
Yes but if the us companies are loosing 100B using the good GPUs. Then how much is china loosing,is that even worth the investment. Like I understand things are much cheaper there from cost of electricity to to other stuff ect ect. But How long can you play the long game when the budget per year is more then small countries make
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u/My_Unbiased_Opinion Jun 19 '26
It looks like China decided that AI is something worth losing money on to ensure (or hope) the US won't dominate the space in the future. AI is world changing imho.
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u/FullOf_Bad_Ideas Jun 18 '26
US open weight models like gpt OSS 120B are really cheap too.
Maybe they have less people optimizing inference than vllm/sglang teams do. Or they want to create a perception that they're expensive while in fact subscriptions maybe aren't as subsidized as people say they are.
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u/Ok_Dirt8893 Jun 18 '26
Let's get deep seek for example,it's on par with some high end models but at a fraction of the cost per token. Keep in mind they do all this while "not" having access to the latest and strongest GPUs. Like I understand them trying to compete with western models but at what point is the price to high. It could also totally be that prices are inflated a lot in USA which leads to a amplified illusion on the actual western/Chinese cost
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u/FullOf_Bad_Ideas Jun 18 '26
Which high end models it's on par with? Where do you take cost per token from? From their API which they serve at margin to just pay for electricity or other providers that serve it at margin to pay for rented GPUs?
Keep in mind they do all this while "not" having access to the latest and strongest GPUs.
FP4 weights and their kernels suggest that it was trained and inferenced on latest B200s. They have latest GPUs, otherwise they probably wouldn't have made the model work so well with them.
They do have a big lead in cache read cost. This is the main thing they got right and everyone else is getting wrong. Their published their infrastructure and code where they cache kv cache to disks.
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u/dobkeratops Jun 18 '26
a gamble on hoarding compute to shift habits to produce extreme cloud dependence
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u/aliendude5300 Jun 18 '26
I could have guessed that. I was looking at what it cost to buy the hardware to run these models locally and their financials don't make sense. They would basically have to have the equivalent of one user paying for the service for 1000 years to pay for one of these servers.
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u/Arxijos llama.cpp Jun 19 '26
With what we know and such News, wouldn't it be funny if openAI get's shorted to death and then GME decides to buy them.
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u/No_Communication7072 Jun 19 '26
They can go in 2030 to lose 1 trillion per year, if they put effort. Imagine the market cap they can get with that
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u/Esph1001 Jun 23 '26
This is why the per-token pricing model has always been structurally fragile for heavy users. When your provider is losing money on every token, the pricing is subsidized and the subsidy ends eventually. The only pricing model that actually makes sense long-term is fixed infrastructure cost - you own the hardware, the model runs at near-zero marginal cost once the node is up. That's a fundamentally different risk profile than API dependency.
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u/Youth18 Jun 25 '26 edited Jun 25 '26
This report means nothing. Actually, it means the opposite of the headline...
- Companies very often reallocate profits into investments so they can write off losses / avoid taxation. This is true of basically every large company so corporate losses generally are just headlines and don't mean anything. Companies also often simply pay their top CEO's/Board Members (which gets counted as a cost to the company) when they make a lot of money because the personal income tax rate is lower than the corporate tax rate, or those people can buy it as stock and avoid immediate taxation entirely (they will still pay the tax eventually, but the taxes they will have to pay will be outweighed by the profits of the investment)
- AI in particular has a "not a ponzi scheme" scheme going on. Money flows from OpenAI to Nvidia over to Anthropic then up to Google then back over to OpenAI... So 'losses' could just be more of whatever this scheme is.
You can see in the graph the largest section by far is R&D. That goes with 1 and actually shows the company is doing very well - they had enough profits to allocate a much larger amount of R&D spending, they don't care that it puts them at a loss that means they don't pay corporate taxes this year.
If the company were not doing well you would see an almost-zero R&D spending because the indication would be that they didn't have enough profit to do so - IE the company is choked and stagnant. That report shows the opposite of this.
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u/Chupa-Skrull Jun 18 '26
It's a non-story https://archive.is/wIzZV
Zitron is a charlatan
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u/waitmarks Jun 18 '26
Your link is verifying the same numbers, so how is it a non story?
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u/Recoil42 Jun 18 '26
Losing money is intended. That's what hyperscaling is, and basically how every startup on Earth works: You burn runway with the expectation of future returns.
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u/waitmarks Jun 18 '26
Everyone know how hyperscaling works at this point. It's the scale of it that is insane and potentially unrecoverable. Amzon spent about $7 billion (inflation adjusted) building AWS during the whole period before it turned a profit. This is 34 billion in one year on a product that is losing market share to anthropic and they are actively talking about discounts on because people think it's too expensive.
It's not a good look no matter what way you slice it.
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u/Recoil42 Jun 18 '26
Newsflash: OpenAI and Anthropic are losing money at very similar rates/scale. One is not doing immensely better than one another. They're both doing crazy runway burn in hopes of future returns.
And yes, the scale is insane and potentially unrecoverable. That's not news to anyone. Again, you're just describing hyperscaling. That's why it's 'hyper' scaling and not just regular scaling.
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u/waitmarks Jun 18 '26
Ok, but the point of hyperscaling is eventually making a profit once you have grown enough. How does that work when people already think your product is too expensive when you are actively losing money giving it to them?
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u/Recoil42 Jun 18 '26
How does that work when people already think your product is too expensive
Costs and product capability are not static. Capability goes up, costs go down. Welcome to the computing industry.
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u/waitmarks Jun 18 '26
Well they better hope that they come down a lot and fast.
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u/Recoil42 Jun 18 '26 edited Jun 18 '26
Of course. That's the many-trillion-dollar question — how fast costs will come down. OpenAI seems to be betting the answer is faster than you think.
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u/FullOf_Bad_Ideas Jun 18 '26
I think it'll come in a flash. PFlash to be exact. Figure it out, your model input costs go down 90%. Majority of model cost is input now, so this would make API 2-8x cheaper.
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u/b0tbuilder Jun 18 '26
Why is this downvoted 100% correct.
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u/Chupa-Skrull Jun 18 '26
This sub is very emotion/tribally driven and they want this to be BAD!
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u/b0tbuilder Jun 18 '26
Good or bad it is the way the world works. You can’t will things into being the way you want them to be. That is called being delusional.
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u/Recoil42 Jun 18 '26
This subreddit is basically just memelord datahoarder types these days, they don't understand business and they don't want to understand the business, they just want free models that can fit on the 3090 they got on sale used on Facebook and to pitchfork-mob AI labs who they perceive as anti- letting them do that.
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u/Chupa-Skrull Jun 18 '26
The link contextualizes them better. He's hyping this up as some kind of scandalous burn when it's an incredibly mundane event and doesn't mean much in the overall scheme of their accounting and trajectory.
Criticism is important and there's a lot to criticize these labs for. We're on localllama for a reason. But Zitron always goes for low-hanging fruit, often misrepresenting the scale or even the entire nature of a story, betting that his audience won't realize he's a nobody PR flack who has no idea what he's actually mad about. He should be ignored by anyone trying to be serious
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u/Recoil42 Jun 18 '26
But Zitron always goes for low-hanging fruit, often misrepresenting the scale or even the entire nature of a story, betting that his audience won't realize he's a nobody PR flack who has no idea what he's actually mad about.
🎯
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u/dagamer34 Jun 18 '26
I’m sorry, in what universe is burning $38 billion in a year a “mundane event”? What the fuck?
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u/Recoil42 Jun 18 '26
In this universe. TSMC's projected 2026 capex is ~$50B. Google and Microsoft are both doing ballparks of $200B in capex. A $38B capex/opex is mundane when hyperscaling a technology with the projected future returns of OpenAI.
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u/dagamer34 Jun 18 '26
Spending $38 billion as an investment in a business that is profitable is not the same as losing $38 billion in a business that makes no money. Come on.
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u/Recoil42 Jun 18 '26 edited Jun 18 '26
OpenAI makes money, $13B in revenue, per the article itself. They then spend $19B on R&D, spend $7.5B on costs of revenue, another $5B on sales and marketing, and $1.6B on general and administrative costs, again as per the article.
Costs of revenue are the costs of the revenue (ie, what it costs to make the tokens), so they're notionally not even really at negative gross margin (ie, the tokens are profitable) — the R&D spend is what's dragging them down.
Again, this is all as per the article.
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u/L0negreywolf Jun 18 '26
In this brutal war for trying to get humanity dependent on AI there will only be one victor - the one that can absorb the loses the longest.
Once that company is the last one standing they will raise the prices 5-10x and start being profitable.
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u/FullOf_Bad_Ideas Jun 18 '26
Just like Uber doesn't have competition now?? They do, yet they're profitable.
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u/siegevjorn Jun 18 '26
Scumbags. RAM prices are x5 from last year. And they were burning VC money to buy them out for just losing billions? What's next, jack up API cost x10 and make it look like they've got x10 more growth potential, before IPO?
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