Both will do public reporting only when they IPO[4] and have regulatory requirement to do so every quarter. For private companies[1] reporting to investors there are no fixed rules really[3]
Even for public companies, there is fair amount of leeway on how GAAP[2]expects recognize revenue. The two ways you highlight is how you account for GMV- Gross Merchandise Value.
The operating margin becomes very less so multiples on absolute revenue gets impacted when you consider GMV as revenue.
For example if you consider GMV in revenue then AMZN only trades at ~3x ($2.25T/$~800B )to say MSFT($2.75T/$300B) and GOOG ($3.4T/$400B) who both trade at 9x their revenue.
While roughly similar in maturity, size, growth potential and even large overlap of directly competing businesses, there is huge (3x / 9x) difference because AMZN's number includes with GMV in retail that GOOG and MSFT do not have in same size in theirs.
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[1] There are still a lot of rules reporting to IRS and other government entities, but that information we (and news media) get is from investors not leaks from government reporting - which would be typically be private and illegal to disclose to public.
[2] And the Big 4 who sign off on the audit for companies prefer to account for it.
[3] As long as it is not explicit fraud or cooking the books, i.e. they are transparent about their methods.
[4] Strictly this would be covered in the prospectus(S-1) few weeks before going public and that is first real look we get into the details.
They aren't reporting anything yet. What we hearing is just from news media who get their leaks/info from investors who get some form of IR reports/ presentation.
The $24b figure is literally in OpenAI's announcement.The $19b ARR and $6b added in Feb came directly from Anthropic CEO recently.
What we hearing is just from news media who get their leaks/info from investors who get some form of IR reports/ presentation.And? That's not a legislated report; they can use whatever mechanism they want to, without disclosure, to produce numbers.
Lets wait until they are regulated as a public company, then their mechanism has to be both aligned with what legislation requires as well as clearly documented in their report.
That would be fraud against whoever participated in this round, so no. Just because they aren't regulated doesn't mean they are literally free to do whatever they want to close the round.
When we say reporting it means there are statutory submissions with an auditor signing off, with legal liability. As the other reply referenced consequences for doing this incorrectly can be severe - Arthur Anderson is no more after all because of Enron.
A Press Release (of a private entity) does not have to satisfy this high bar.
Press release does mean no constraints, for public companies, disclosure of important information by officers and other insiders have strong controls. Even if its the just a rocket/poop emoji on a casual social media platform. Lawyers have to refile with the SEC in the expected format. Even private companies have restrictions on not claiming things fraudulently to investors, but these are accredited investors with lesser controls than retail.
https://www.benzinga.com/markets/tech/26/03/51248353/michael...
Real question: What is the real impact of this rule change? To me, it seems so minor. Three months is just a blip in time for any long term investor.
> which corruptly will force us all to buy into these companies
Why is this "corrupt"? That term makes no sense here.Also, if you don't like the NASDAQ 100 rules, then you don't have to invest in securities that track it. You can trade the basket yourself minus the names that you don't like.
Finally, I would say that S&P 500 index is far more important than NASDAQ 100. To join the S&P 500 index, the name must be profitable for the most recent year. (four quarters). Recall that Uber IPO'd in 2019, but was not profitable until 2023. OpenAI probably will not be profitable when it goes public; thus, it will not join the S&P 500 immediately.
I think the bigger story is SpaceX. It will likely IPO very close to a 1T USD market cap (with a small float: ~10%). And, thanks to StarLink, I assume that SpaceX is now wildly profitable.
Isn't the idea with the indexes that they allow you to intentionally not take an activist position in the market? The exposure is not tied to any underlying market hypothesis. In other words, if we make people form a market hypothesis in order to decide whether or not to hold this index, it has failed in its purpose.
More likely than not, most of us are already holding stock in these companies one way or another. All the Mag 7 hold a major chunk of OAI and Anthropic stock anyway, slower entry does not make it less risky for us.
Even if the big tech companies did not hold any stock, they are still the biggest vendors and their own order books is hugely impacted by the AI demand from these two ( and others in this space), either way we are all in this together.
Doubt it.
The world does not allow perfect competition.
However in the long term, economics usually finds the most efficient way.
Maintaining inefficient structures like tariffs or monopolies becomes more and more expensive and eventually untenable and disruptions will occur.
Really feels like 1928
Passive investments are good, but if taken too far as they clearly have been in the last decade they become a scam. Everyone is SIPing into it, and there is infinite liquidity. Until one big whale finally decides they are booking it, then all hell will break loose on the same damn day.
You can just choose not to play the accounting game, and only choose the ones that actually gaap viable as investment opportunities. For example mag7 - tesla are all relatively cheap when they dip.
Some times the best play is just not to play. If you think they are too risky, walk away. There are enough good oppotunities
> mag7 (minus) tesla are all relatively cheap when they dip
I asked ChatGPT for a list of Magnificent 7 stocks and their most recent price to earnings (PE) ratios. Company Ticker P/E Ratio
Apple Inc. AAPL ~33
Microsoft Corporation MSFT ~25
Alphabet Inc. GOOGL ~29
Amazon.com Inc. AMZN ~30
NVIDIA Corporation NVDA ~38
Meta Platforms Inc. META ~28
Tesla Inc. TSLA ~378
In the last 50 years, I think the median PE ratio for S&P 500 index is about 15. Seven and below is considered rock bottom, and 30 and above is very high. These PE ratios look pretty damn high to me.How much do these names need to "dip" for you to consider them cheap?
The numbers OpenAI gave in the post would mean a 30x multiple pre-money. And the $20B -> $24B run-rate growth since the start of the year could plausibly mean anything from 110% to 200% annualized growth rate, depending on whether that happened over two or three months. The $24B is a lower bound as well, since they only gave use one significant digit for the monthly revenue.
I do see less quality from reasoning at chatgpt compared to Gemini but otherwise i'm not seeing a year or years gap.
let's not forget that these major LLMs are all the children of corporate hyper-piracy en masse, none of them are ethical even in origin unless you're talking about the pre-product company charter kind of ethics, like google .
That makes a little more sense, because the number of subscribers are so low that tripling won't really make much difference in terms of turning a profit.
E.g. what good is 20 billion per year when "OpenAI is targeting roughly $600 billion in total compute spending through 2030". That is $150 billion per year?
Assets are harder to measure. Facebook used to say something silly like every user was worth $100. That sounded ridiculous for a completely free app but over a decade later, the company is worth more than that. Revenue is an easier way of measuring assets than profit.
Profit doesn't really matter. It gets taxed. But it's not about dodging taxes; it's because sitting on a pile of money is inefficient. They can hire people. They can buy hardware. They can give discounts to users with high CLTV. They can acquire instead of building. It's healthy to have profit close to $0, if not slightly negative. If revenues fall or costs increase, they can make up for the difference by just firing people or cutting unprofitable projects.
Also when they're raising money, it makes absolutely no sense to be profitable. If they were profitable, why would they raise money? Just use the profits.
Profit is money you couldn’t figure out how to spend. During growth, you want positive operating margins with nominal profits. When the company/market matures, you want pure profits because shareholders like money. If you can find a way to invest those profits in new areas of growth, that’s better.
Profit is the money showing your business is sustainable. Ever since the ZIRP era US companies keep haemorrhaging money at a rate that is physically impossible to recoup.
If OpenAI plans to lose 100+ billion dollars per year for half a decade, what profits are you talking about to offset the losses?
> When the company/market matures, you want pure profits because shareholders like money.
Ah yes. Shareholders like money. And not, you know, basic accounting like "we need money to actually pay salaries, pay for equipment and offices etc. without perpetually relying on seeming endless investor money".
You don’t need profit to offset the losses.
You can simply reduce spending / expenses.
One does not “simply” reduce spending.
Why does stock price go up after mass layoffs?
Everyone wants to treat OpenAI like a car wash business where they need to make a profit almost immediately. I don’t know why people can’t understand that the industry is in a rapid growth stage and investing the money is more important than making a profit now. The profits will come later.
Since everyone is trying to get compute from anywhere they can, including OpenAI going to Google, it's hard to tell what is used internally vs externally.
For example, it's entirely possible that Google's internal roadmap for Gemini sees it using $600b of compute through 2030 as well. In that case, OpenAI needs to match since compute is revenue.
So the same money spent by OpenAI and Google doesn't carry nearly the same amount of risk?
OpenAI doesn't?
Why not? They've openly said they could in theory sell compute to others if they can't use it all.Why are we saying that OpenAI and Anthropic can't do the same?
I remain skeptical of Uber.
Sure, maybe OpenAI and Anthropic will make it work. It's not impossible. But it's far from guaranteed.
Uber generates about $1b in profit yearly now.
Openai can't claim either.
Uber was only on a path to monopoly in the US, not world wide. It’s lost to local competitors in most countries. And it can get disrupted by self driving cars soon.
OpenAI’s SOTA LLM training smells like a natural monopoly or duopoly to me. The cost to train the smartest models keep increasing. Most competitors will bow out as they do not have the revenue to keep competing. You can already see this with a few labs looking for a niche instead of competing head on with Anthropic and OpenAI.
Distilling might only be effective in the chat bot dominant era. We are about to move to an agents era.
Furthermore, I’m guessing distilling will get harder and harder. Claude Code leak shows some primitive anti distilling methods already. There’s research showing that models know when it’s being benchmarked. Who’s to say Anthropic and OpenAI aren’t able to detect when their models are being distilled?
Yes
>before making a profit.
No
The problem for OpenAI is that the cost of getting them where they are now has been to high and competitors can now establish themselves for much less money.
The dame Uber that lost close to 30 billion dollars over 10 years to subsidize its price dumping?
No, no we are not treating OpenAI differently than Uber
the expectation is that they'll eventually make money. they can't raise forever. only startups are not profitable for a few years. but most companies that have existed for a long while have been profitable
and since they're expected to make a LOT of money, everyone wants a piece of that future pie, pushing up the valuation and amount raised to admittedly somewhat delusional levels like here
In this case because it's not clear that anybody has actually figured out how to sell inference for more than it costs
Whether GPT-5 was profitable to run depends on which profit margin you’re talking about. If we subtract the cost of compute from revenue to calculate the gross margin (on an accounting basis),2 it seems to be about 30% — lower than the norm for software companies (where 60-80% is typical) but still higher than many industries.
(They go on to point out that there are other costs that might mean they didn't break even on other costs - although I suspect these costs should be partially amortized over the whole GPT 5.x series, not just 5.0)
https://epochai.substack.com/p/can-ai-companies-become-profi...
https://martinalderson.com/posts/are-openai-and-anthropic-re... (with math working backwards from GPU capacity)
"Most of what we're building out at this point is the inference [...] We're profitable on inference. If we didn't pay for training, we'd be a very profitable company"
https://simonwillison.net/2025/Aug/17/sam-altman/
"There’s a bright spot, however. OpenAI has gotten more efficient at serving paying users: Its compute margin—the revenue left after subtracting the cost of running AI models for those customers—was roughly 70% in October, an increase from about 52% at the end of last year and roughly 35% in January 2024."
https://archive.is/OqIny#selection-1279.0-1279.305 (Note this is after having to pay higher spot rates for compute because of higher than expected demand)
That is not, in fact, "well known", but based entirely on the announcements of the inference providers themselves who also get very cagey when asked to show their work and at least look like they're soliciting a constant firehose of investment money simply to keep the lights on. In particular there's a troubling tendency to call revenue "recurring" before it actually, you know, recurs.
I mean sure, it's self reported.
But the inference prices somewhere like Fireworks or TogetherAI charges is comparable to what Google/AWS/Azure charge for the same model an we know they aren't losing money - they have public accounts that show it, eg:
https://au.finance.yahoo.com/news/wall-street-resets-amazon-...
Fireworks’ gross margin—gross profit as a percentage of revenue—is roughly 50%, according to the same person
https://archive.is/Y26lA#selection-1249.65-1249.173
> In particular there's a troubling tendency to call revenue "recurring" before it actually, you know, recurs.
If someone has a subscription then yes that is pretty normal.
Not if you've substantively changed rate limits 3 times in the last 5 months while still counting those forecast revenues. In most industries that's called rug-pulling.
profit isn't a function of having a killer product, it's a function of having no competition
Industries always consolidate and winners emerge. SOTA LLMs look like a natural monopoly or duopoly to me because the cost to train the next model keeps going up such that it won't make sense for 20 competitors to compete at the very high end.
TSMC is a perfect example of this. Fab costs double every 4 years (Rock’s Law). It's almost impossible to compete against TSMC because no one has the customer base to generate enough revenue to build the next generation of fabs - except those who are propped up by governments such as Intel and Rapidus. Samsung is basically the SK government.
I don’t see how companies can catch OpenAI or Anthropic without the strong revenue growth.
It's believable that Meta, ByteDance, etc. can catch up too. It is not certain that scaling will meaningfully increase performance indefinitely, and if it stops soon, they surely will. Furthermore, other market conditions (US political instability) can enable even more labs, like Mistral, to serve as compelling alternatives.
Uber, TSMC, etc. have strong moats in the form of physical goods and factories. LLMs have nothing even remotely comparable. The main moat is in knowledge, which is easy to transfer between labs. Do you think all the money that goes into training a model goes into the actual final training run? No, it is mostly experiments and failed ideas, which do not have to be repeated by future labs and offshoots.
It's certain that it won't. We've already hit diminishing returns.
I’ll be polite and call this statement ‘a very debatable’ one.
Only one company on Earth can make the UV lithography machines TSMC buys for their highest end fabs, and they're not selling to anyone else.
The PRC tried to brute force this supply chain backed by the full might of the Party's blank check, all red tape cut, literally the best possible duplication scenario, and they failed.
no, most industries just sell boring generic products, a few industries favor monopolists. Semiconductors are one of them but LLMs are also as far removed from that business as is physically possible.
TSMC makes the most complicated machines humans have ever built, a LLM requires a few dozen nerds, a power plant, a few thousand lines of python and chips. That's why if you're Elon Musk you could buy all of the above and train yourself an LLM in a month.
LLMs are comically simple pieces of software, they're just big. But anyone with a billion dollars can have one, they're all going to be commoditized and free in due time, like search. Copying a lithography machine is difficult, copying software is easy. that's why Google burrowed itself into email, and browsers, and your phone's OS. Problem for openai is they don't have any of that, there's already half a dozen companies that, for 99% of people, do what they do.
Profit is money you can't find a use for to grow your business, so you give some of it to the government in the form of tax.
Also there is a big difference between operational expenses and capital expenses like building data centers.
I think OpenAI is being very aggressive on the growth vs conservative financial management spectrum but just saying "only profit should matter" is just wrong.
It's what attracts capital investment, which businesses need
As did Amazon, Google, Meta etc etc.
Could be wrong though.
Even a simple shop isn't profitable for months if it needs to buy stock up front, and run some ads to let people know about it. The money for that comes from the shop owners as an investment.
This is the same thing but on a slightly bigger scale, over a longer time frame.
US tech companies just continue operating because "revenue and growth".