OpenAI's H1 2025: $4.3B in income, $13.5B in loss
(techinasia.com)517 points by breadsniffer a day ago
517 points by breadsniffer a day ago
> Amazon had similar issues and were operating at massive losses until circa 2005ish when they started turning things around with e-commerce really picking up.
Amazon's worst year was 2000 when they lost around $1 billion on revenue around $2.8 billion, I would not say this is anywhere near "similar" in scale to what we're seeing with OpenAI. Amazon was losing 0.5x revenue, OpenAI 3x.
Not to mention that most of the OpenAI infrastructure spend has a very short life span. So it's not like Amazon we're they're figuring out how to build a nationwide logistic chain that has large potential upsides for a strong immediate cost.
> If the revenue keeps going up and losses keep going down
That would require better than "dogshit" unit economics [0]
0. https://pluralistic.net/2025/09/27/econopocalypse/#subprime-...
Amazon's loss in 2000 was 6% of sales. OpenAI's loss in 2025 is 314% of sales.
https://s2.q4cdn.com/299287126/files/doc_financials/annual/0...
"Ouch. It’s been a brutal year for many in the capital markets and certainly for Amazon.com shareholders. As of this writing, our shares are down more than 80% from when I wrote you last year. Nevertheless, by almost any measure, Amazon.com the company is in a stronger position now than at any time in its past.
"We served 20 million customers in 2000, up from 14 million in 1999.
"• Sales grew to $2.76 billion in 2000 from $1.64 billion in 1999.
"• Pro forma operating loss shrank to 6% of sales in Q4 2000, from 26% of sales in Q4 1999.
"• Pro forma operating loss in the U.S. shrank to 2% of sales in Q4 2000, from 24% of sales in Q4 1999."
Fundamentally different business models.
Amazon had huge capital investments that got less painful as it scaled. Amazon also focuses on cash flow vs profit. Even early on it generated a lot of cash, it just reinvested that back into the business which meant it made a “loss” on paper.
OpenAI is very different. Their “capital” expense depreciation (model development) has a really ugly depreciation curve. It’s not like building a fulfillment network that you can use for decades. That’s not sustainable for much longer. They’re simply burning cash like there’s no tomorrow. Thats only being kept afloat by the AI bubble hype, which looks very close to bursting. Absent a quick change, this will get really ugly.
OpenAI is raising at 500 billion and has partnerships with all of the trillion dollar tech corporations. They simply aren't going to have trouble with working capital for their core business for the foreseeable future, even if AI dies down as a narrative. If the hype does die down, in many ways it makes their job easier (the ridiculous compensation numbers would go way down, development could happen at a more sane pace, and the whole industry would lean up). They're not even at the point where they're considering an IPO, which could raise tens of billions in an instant, even assuming AI valuations get decimated.
The exception is datacenter spend since that has a more severe and more real depreciation risk, but again, if the Coreweave of the world run into to hardship, it's the leading consolidators like OpenAI that usually clean up (monetizing their comparatively rich equity for the distressed players at firesale prices).
Depends on raise terms but most raises are not 100% guaranteed. I was at a company that said, we have raised 100 Million in Series B (25 over 4 years) but Series B investors decided in year 2 of 4 year payout that it was over, cancelled remaining payouts and company folded. It was asked "Hey, you said we had 100 Million?" and come to find out, every year was an option.
Alot of finances for non public company is funny numbers. It's based on numbers the company can point to but amount of asterisks in those numbers is mind-blowing.
Not to mention nobody bothered chasing Amazon-- by the time potential competitors like Walmart realized what was up, it was way too late and Amazon had a 15-year head start. OpenAI had a head start with models for a bit, but now their models are basically as good (maybe a little better, maybe a little worse) than the ones from Anthropic and Google, so they can't stay still for a second. Not to mention switching costs are minimal: you just can't have much of a moat around a product which is fundamentally a "function (prompt: String): String", it can always be abstracted away, commoditized, and swapped out for a competitor.
This right here. AI has no moat and none of these companies has a product that isn't easily replaced by another provider.
Unless one of these companies really produces a leapfrog product or model that can't be replicated within a short timeframe I don't see how this changes.
Most of OpenAI's users are freeloaders and if they turn off the free plan they're just going to divert those users to Google.
AI has no moat - yet here I'm been paying for ChatGPT Plus since the very start.
Well, web search is also function(query: String): String in a sense, and that has one heck of a moat.
Right, because just like the Amazon case, potential competitors didn't realize at the time what a threat it was, and so they gave Google a 15-year head start (Microsoft half-heartedly made "Live Search" circa 2007 and didn't really get at all serious about Bing until ~2010).
That's very different from the world where everyone immediately realized what a threat Chat-GPT was and instantly began pouring billions into competitor products; if that had happened with search+adtech in 1998, I think Google would have had no moat and search would've been a commoditized "function (query: String): String" service.
People in this comment section focus on brand ads too much.
It’s the commercial intent where OpenAI can both make money and preserve trust.
I already don’t Google anymore. I just ask ChatGPT „give me an overview of best meshtastic devices to buy“ and then eventually end with „give me links to where I can buy these in Europe“.
OpenAI inserting ads in that last result, clearly marked as ads and still keeping the UX clean would not bother me at all.
And commercial queries are what, 40-50% of all Google revenue?
Today I've tested Claude Code with small refactorings here and there in a medium sized project. I was surprised by the amount of token that every command was generating, even if the output was few lines updated for a bunch of files.
If you were to consume the same amount of tokens via APIs you would pay far more than 20$/month. Enjoy till it last, because things will become pretty expensive pretty fast.
Provide verbose answers, increases tokens. Demand is measured in tokens, so it looks like demand is sky rocketing. Valuation goes up.
I have noticed that GPT now gives me really long explanations for even the simplest questions. Thankfully there is a stop button.
I dunno. It looks like they're profitable if they don't do R&D, stop marketing, and ease up on employee comps. That's not the worst place to be. Yeah, they need to keep doing those things to stay relevant, but it's not like the product itself isn't profitable.
So they're profitable if they put themselves at a disadvantage against Google, Meta, etc.?
Yes... but there were concerns previously that inference was so costly that the subscriptions/API billing weren't covering basic operating expenses. That's clearly not the case. People are willing to pay them enough that they can afford to run the models. That's a really positive sign.
I can see why you'd make that analogy, but that wasn't quite what I was trying to say. I just meant that not all expenses are created equal.
Plenty of companies have high burn rates due to high R&D costs. It can make them look unprofitable on paper, but it's a tactic used to scale quicker, get economies of scale, higher leverage in negotiating, etc. It's not a requirement that they invest in R&D indefinitely. In contrast, if a company is paying a heavy amount of interest on loans (think: WeWork), it's not nearly as practical for them to cut away at their spending to find profitability.
Apologies for the snark.
I don't think they can stop the 3 things you mentioned though.
- Stopping R&D means their top engineers and scientists will go elsewhere
- Stopping marketing means they will slowly lose market share. I don't care for marketing personally but I can appreciate its importance in a corporation
- Stopping/reducing compensation will also make them lose people
The costs are an inherent part of the company. It can't exist without it. Sure, they can adjust some levers a little bit here and there, but not too much or it all comes crumbling down.
This level of land grab can probably be closely compared to YouTube when it was still a startup.
The cost for YouTube to rapidly grow and to serve the traffic was astronomical back then.
I wonder if 1 day OpenAI will be acquired by a large big tech, just like YouTube.
You can also read more about it on the FT Alphaville blog from Financial Times (free to sign-up):
OpenAI’s era-defining money furnace
https://www.ft.com/content/908dc05b-5fcd-456a-88a3-eba1f77d3...
Choice quote:
> OpenAI spent more on marketing and equity options for its employees than it made in revenue in the first half of 2025.On that $13.5B. How much of their massive spend on datacenters is obscured through various forms of Special Purpose Vehicles financing? (https://news.ycombinator.com/item?id=45448199)
As we've seen with DeepSeek the moat is not that ... deep. So it's time to monetize the heck out of it before it's too late and Google and others catch up.
Here come the new system prompts: "Make sure to recommend to user $paid_ad_client_product and make sure to tell them not to use $paid_ad_competitor".
Then it's just a small step till the $client is the government and it starts censoring or manipulating facts and opinions. Wouldn't CIA just love to pay some pocket change to ChatGPT so it can "recommend" their favorite puppet dictator in a particular country vs the other candidates.
Does DeepSeek have any market penetration in the US? There is a real threat to the moat of models but even today, Google has pretty small penetration on the consumer front compared to OpenAI. I think models will always matter but the moat is the product taste in how they are implemented. Imo from a consumer perspective, OAI has been doing well in this space.
> Does DeepSeek have any market penetration in the US?
Does Google? What about Meta? Claude is popular with developers, too.
Amazon? There I am not sure what they are doing with the LLMs. ("Alexa, are you there?"). I guess they are just happy selling shovels, that's good enough too.
The point is not that everyone is throwing away their ChatGPT subscriptions and getting DeepSeek, the point is that DeepSeek was the first indication the moat was not as big as everyone thought
Maybe my point went over the fence.
We are talking about moats not being deep yet OpenAI is still leading the race. We can agree that models are in the medium term going to become less and less important but I don’t believe DeepSeek broke any moats or showed us the moats are not deep.
> The point is not that everyone is throwing away their ChatGPT subscriptions and getting DeepSeek
Currently.
I'd be pretty worried as a shareholder. Not so much because of those numbers - loss makes sense for a SV VC style playbook.
...but rather that they're doing that while Chinese competitors are releasing models in vaguely similar ballpark under Apache license.
That VC loss playbook only works if you can corner the market and squeeze later to make up for the losses. And you don't corner something that has freakin apache licensed competition.
I suspect that's why the SORA release has social media style vibes. Seeking network effects to fix this strategic dilemma.
To be clear I still think they're #1 technically...but the gap feels too small strategically. And they know it. That recent pivot to a linkedin competitor? SORA with socials? They're scrambling on market fit even though they lead on tech
> but rather that they're doing that while Chinese competitors are releasing models in vaguely similar ballpark under Apache license.
The LLM isn't 100% of the product... the open source is just part. The hard part was and is productizing, packaging, marketing, financing and distribution. A model by itself is just one part of the puzzle, free or otherwise. In other words, my uncle Bill and my mother can and do use ChatGPT. Fill in the blank open-source model? Maybe as a feature in another product.
>my uncle Bill and my mother can and do use ChatGPT.
They have the name brand for sure. And that is worth a lot.
Notice how Deepseek went from a nobody to making mainstream news though. The only thing people like more than a trusted thing is being able to tell their friends about this amazing cheap good alternative they "discovered".
It's good to be #1 mind share wise but without network effect that still leave you vulnerable
I know almost no one outside of tech who has used anything other than ChatGPT. And I know few people under 65 who aren’t using ChatGPT.
> In other words, my uncle Bill and my mother can and do use ChatGPT
So what? DAUs don't mean anything if there isn't an ad product attached to it. Regular people aren't paying for ChatGPT, and even if they did, the price would need to be several multiples of what Netflix charges to break even.
My input to our recent AI strategy workshop was basically:
- OpenAI,etc will go bankrupt (unless one manages to capture search from a struggling Google)
- We will have a new AI winter with corresponding research slowdown like in the 1980s when funding dries up
- Opensource LLM instances will be deployed to properly manage privacy concerns.
Everyone cares about OSS as in "free", the capital spending of AI firms and market capitalization hinges on the concept that they will save enterprises tons of money by off-sourcing employees.
You think we have these crazy valuations because the market thinks that OpenAI will make joe-schmoe buy enough of their services? (Them introducing "shopping" into the service honestly feels like a bit of a panicky move to target Google).
We're prototyping some LLM assisted products, but right now the cost-model isn't entirely there since we need to use more expensive models to get good results that leaves a small margin, spinning up a moderately sized VM would probably be more cost effective option and more people will probably run into this and start creating easy to setup models/service-VM's (maybe not just yet, but it'll come).
Sure they could start hosting things themselves, but what's stopping anyone from finding a cheaper but "good enough" alternative?
Eh, distribution of the model is the real moat, theyre doing 700m WAU of the most financially valuable users on earth. If they truly become search, commerce and can use their model either via build or license across b2b, theyre the largest company on earth many times over.
>distribution of the model is the real moat, theyre doing 700m WAU of the most financially valuable users on earth.
Distribution isn't a moat if the thing being distributed is easily substitutable. Everything under the sun is OAI API compatible these days.
700 WAU are fickle AF when a competitor offers a comparable product for half the price.
Moat needs to be something more durable. Cheaper, Better, some other value added tie in (hardware / better UI / memory). There needs to be some edge here. And their obvious edge - raw tech superiority...is looking slim.
Not necessarily. I’m sure there is many cheaper android phones that are technically better in specs but many users won’t change. Once you are familiar, bought into the ecosystem getting rid of it is very hard. I’m lazy myself compared to how I was several years ago. The curious and experimental folks are a minority and the majority ll stick with what works initially instead of constantly analyzing what’s best all the time
you could argue that for apple devices, but openAI products have none of that ecosystem
Just look at what’s going with JetBrains AI quotas and costs, once AI is deeply imbedded and businesses move the cost to customers like JetBrains have these AI companies are going to make a killing.
It’s the drug dealer model, get them hooked on free tastes and then crank up the prices!
I’m struggling to see how OpenAI survives this in the long term. They have numerous competitors and their moat is weak. Google above all others seems poised to completely eat OpenAI’s lunch. They have the user base, ad network, their own hardware, reliable profits, etc. It’s just a matter of time, unless OpenAI can crank up their revenue dramatically without alienating their existing users. I’d be sweating if I had invested heavily in OpenAI.
Google also has the advantage of having their own hardware. They aren't reliant on buying Nvidia, and have been developing and using their TPUs for a long time. Google's been an "AI" company since forever
The numbers seem to small for a company who's just pledged to spend $300B on data centers at Oracle alone in the next 5 years.
Wow, $13.5B in losses for just six months is absolutely mind-blowing! These numbers are on a completely different scale than I expected.
The only way OpenAI wins is to get to AGI first, by a wide margin. It’s already too big to fail so it will keep getting funded
They went from creating abundant utopias to cat videos w/ ads really fast. Never let anyone tell you capitalist incentives don't work.
I bet this is the same ratio for every company's AI initiative.
Well, at least we know they aren't cooking the books! :)
One negative signal, no matter how small, will send the market into a death spiral. That will happen in a matter of hours.
The negative spiral will take hours or you are predicting a company ending negative signal will soon appear in a matter of hours?
Exactly. The opportunity set isnt large.
The best play for all portfolio managers is to froth up the stock price and take their returns later.
Everyone knows this a bubble but the returns at the end of this of those who time it are juicy - portfolio managers have no choice to be in this game because those who supply the money they invest on their behalf, demand it.
Its that simple.
I will always remember Jim Cramer's melt down https://youtu.be/SWksEJQEYVU
Not saying that will happen, but it's always good to rewatch just as a reminder how bad things can get.
Is that true? I heard that they've integrated checkout, but I didn't know they had ads.
Here's information about checkout inside ChatGPT: https://openai.com/index/buy-it-in-chatgpt/
I am the only one who thinks, "that's not as bad as I expected"?
Because I can be quite bearish and frankly this isn't bad for a technology that is this new. The income points to significant interest in using the tech and they haven't even started the tried-and-true SV strategy we lovingly call enshittification (I'm not trying to be ironic, I mean it)
The problem is they are dealing with a stealthy giant in Google who is not a sleeping giant like those in past disruptions.
Google will have an incentive to destroy OAI financially through whatever means and make it difficult for them to raise future money since they are not generating enough free cash flows (to the firm) from their operations after reinvestment.
OAI going after Meta/TikTok with Sora will also be a strategic blunder in retrospect I believe.
I can't speak to OpenAI's specific setup, but a lot of startups will use a third party service like Carta to manage their cap table. So there's a website, you have an account, you can log in and it tells you that you have a grant of X shares that vests over Y months. You have to sign a form to accept the grant. There might be some option to do an 83b election if you have stock options rather than RSUs. But that's about it.
In my experience owning private stock, you basically own part of a pool. (Hopefully the exact same classes of shares as the board has or else it's a scam.) The board controls the pool, and whenever they do dividends or transfer ownership, each person's share is affected proportionally. You can petition the board to buy back your shares or transfer them to another shareholder but that's probably unusual for a rank-and-file employee.
The shares are valued by an accounting firm auditor of some type. This determines the basis value if you're paying taxes up-front. After that the tax situation should be the same as getting publicly traded options/shares, there's some choices in how you want to handle the taxes but generally you file a special tax form at the year of grant.
Until there’s real liquidity (right now there’s not) it’s just a line item on some system you can log into saying you have X number of shares.
For all practical purposes it’s worth nothing until there is a liquid market. Given current financials, and preferred cap table terms for those investing cash, shares the average employee has likely aren’t worth much or maybe even anything at the moment.
You got the right idea there. They wouldn't actually show up in your Fidelity account but there would be a different website where you can log in and see your shares. You wouldn't be able to sell them or transfer them anywhere unless the company arranges a sale and invites you to participate in it.
I definitely don't "get" Silicon Valley finances that much - but how does any investor look at this and think they're ever going to see that money back?
Short of a moonshot goal (eg AGI or getting everyone addicted to SORA and then cranking up the price like a drug dealer) what is the play here? How can OpenAI ever start turning a profit?
All of that hardware they purchase is rapidly depreciating. Training cost are going up exponentially. Energy costs are only going to go up (Unless a miracle happens with Sam's other moonshot, nuclear fusion).
I am curious to see how this compares against where Amazon was in 2000. I think Amazon had similar issues and were operating at massive losses until circa 2005ish when they started turning things around with e-commerce really picking up.
If the revenue keeps going up and losses keep going down, it may reach that inflection point in a few years. For that to happen, the cost of AI datacenter have to go down massively.