How OpenAI uses complex and circular deals to fuel its multibillion-dollar rise

Here is a charitable perspective on what's happening:

- Nvidia has too much cash because of massive profits and has nowhere to reinvest them internally.

- Nvidia instead invests in other companies that use their gpus by providing them deals that must be spent on nvidia products.

- This accelerates the growth of these companies, drives further lock in to nvidia's platform, and gives nvidia an equity stake in these companies.

- Since growth for these companies is accelerated, future revenue will be brought forward for nvidia and since these investments must be spent on nvidia gpus it drives further lock in to their platform.

- Nvidia also benefits from growth due to the equity they own.

This is all dependent on token economics being or becoming profitable. Everything seems to indicate that once the models are trained, they are extremely profitable and that training is the big money drain. If these models become massively profitable (or at least break even) then I don't see how this doesn't benefit Nvidia massively.

Your conclusion about training being the cost factor that will eventually align with profitability in the inference phases relies on training new models not being an endless arms race.

> Everything seems to indicate that once the models are trained, they are extremely profitable

Some data would reinforce your case. Do you have it?

Here is my data point: "You Have No Idea How Screwed OpenAI Actually Is" - https://wlockett.medium.com/you-have-no-idea-how-screwed-ope...

Yup. Not just Nvidia. Just look at the quarterly results reported by Amazon, Google, Meta, Microsoft and Apple. Each one is reporting revenues never before seen in history. If you make 100 Billion a quarter you have to spend it on something.

These guys are running hyper optimized cash extraction mega machines. There is no comparison to previous bubbles, cause so no such companies ever existed in the past.

If the inference is profitable and training new models is actually an endless arms race that's actually the best outcome for nvidia specifically.

Odd how they are simultaneously having large layoffs even as reporting record revenues.

The question is where the profits are.

Right. As far as I can tell, OpenAI, Grok, etc sell me tokens at a loss. But I am having a hard time figuring out how to turn tokens into money (i.e. increased productivity). I can justify $40-$200 per developer per month on tokens but not more than that.

Inference cost has been going down for a while now. At what point do you think it will be profitable? When cost goes down by 2x? 5x?

This is behind a paywall. Is there a free link you can share ?

100 billion a quarter is Alphabet, right? Given how much click fraud there is, and that every org and business under the sun is held to ransom to feature on the SERP for their own name even — it’s tempting to say Google’s become a private tax on everything.

why would they sell you at a loss when they have been decreasing prices by 2x every year or so for the last 3 years? people wanted to purchase the product at price "X" in 2023 and now the same product costs X costs 10 times less over the years.. do you think they were always selling at a loss?

Amazon - 14,000 layoffs; significant

Microsoft - 14,000 (multiple rounds); significant

Meta - 600 layoffs; insignificant for company size

Google - "Several hundred layoffs"; insignificant for a company size

Apple - No layoffs

Source: https://techcrunch.com/2025/10/24/tech-layoffs-2025-list/

Would love to, and its normally what I do, but archive.is is currently down. At least here from the outer belt.

There’s about 5M software devs in the US so even at $1000/year/person spend, that’s only $5B of revenue to go around. Theres plenty of other uses cases but focusing on pure tech usage, it’s hard to see how the net present value of that equates to multiple trillions of dollars across the ecosystem.

So many such profitable companies are the best possible evidence for the need for drastic antitrust intervention. The lack of competition and regulation is leading to a massive drain on every other sector.

I'm not trying to be annoying, but surely if you'd justify spending $200/developer/month, you could afford $250/month...

The reason I wonder about that is because that also seems to be the dynamic with all these deals and valuations. Surely if OpenAI would pay $30 billion on data centers, they could pay $40 billion, right? I'm not exactly sure where the price escalations actually top out.

The layoffs at Amazon and Microsoft are not due to lack of profits. They’re massively profitable right now.

https://www.macrotrends.net/stocks/charts/MSFT/microsoft/ebi...

https://www.macrotrends.net/stocks/charts/AMZN/amazon/ebitda

Only in the short term.

They're "massively profitable" because they're laying off large portions of a major cost center - labor - and backloading uncoming data center construction costs. As those come due, and labor needs rise again, that profit disappears.

No? That's a 25% expense increase. You just ate the margins on my product/service, and then some.

It's the first new way of interacting with computers since the iPhone. It's going to be massively valuable and OpenAI is essentially guaranteed to be one of the players.

No, Apple also has 100 billion dollars in revenue despite floundering AI and running a very hardware dependent business.

Why is their product not palm? Or windows mobile?

It's not windows mobile because OpenAI was first and is the clear leader in the market. Windows mobile was late to the party and missed their window.

Palm is closer but it's a different world. It's established that Internet advertising companies are worth trillions. It's only in retrospect that what Palm could have been is obvious.

Barring something very unexpected OpenAI is coming out on top. They're prepaying for a good 5-10 years of compute. That means their inference and training for that time are "free" because they've been paid for. They're going to be able to bury their competition in money or buy them out.

This bubble is caused by excess competition. There are 4 large companies who believe that a large new market is being created so each is investing large amounts without any evidence that there will be a single winner that dominates the future market. None of these companies has anything remotely resembling a monopoly except for Amazon in online retail.

How much more was worth USD at the beginning of the year?

Windows mobile by the time it looked like the iPhone was late to the party. But windows had been releasing a mobile os for a long time before that. Microsoft was first, they just didn’t make as good of a product as Apple despite their money.

OpenAI is also first, but it is absolutely not a given that they are the Apple in this situation. Microsoft too had money to bury the competition, they even staged a fake funeral when they shipped windows phone 7.

> Barring something very unexpected

Like the release of an iPhone?

> Nvidia has too much cash because of massive profits and has nowhere to reinvest them internally.

Here's an idea: they could make actual GPUs used for games affordable again, and not have Jensen Huang lie on stage about their performance to justify their astronomical prices. Sure, companies might want to buy them for ML/AI and crash the market again but I'm sure a company of their caliber could solve that if they _really_ wanted to.

Why would they want to do that? The only sector that matter to nvidia is datacenter, its where 90%+ of their profits are. Making their consumer sector even less profitable just seems like a waste of time

I also just don’t understand, as someone with no business experience, how they aren’t just pouring all of that money into enhancing their production capacity. That’s very clearly their bottleneck here.

Yes, I’m certain they are spending an astronomical amount on that already, but why not more? Surely paying more money for construction of more facilities still nets gain even if you run into diminishing returns?

Instead they set up this whacko tax laundering scheme? Just seems like more corporate pocket filling to me, an idiot with no business knowledge.

> Theres plenty of other uses cases

This is where the money is. Anthropic just released claude for excel. If it replaces half of the spreadsheet pushers in the country theyre looking at massive revenue. They just started with coding because theres so much training data and the employees know a lot about coding

Hedging their bets against a potential sudden downturn in consumption of their product, e.g., an AI bubble exploding? If they invest heavily in production capacity only to find that there is not commensurate consumption, then they'll have lost badly.

I'm just confused why people think token-based computing is going to be in such demand in the future. It's such a tiny slice of problems worth solving.

It's like how every big co these days is ML. It will transition to LLMs as well.

Just give it a few years.

The bottleneck is TSMC, who also make chips for almost every other hardware vendor.

TSMC is indeed increasing their production capability as fast as possible, but it's not easy... chip foundries are extremely expensive, complex, and take serious expertise to operate.

It’s called seeding the market. If they can accelerate the growth of potential customers, it will be more profitable than just increasing production to serve existing customers.

Think of exponential growth — would you rather increase the base or the exponent?

It is'nt just nvidia though.

Yep. Same vibes as “ha ha who needs internet connected appliances” (pretty much all appliances are internet connected now). And the apocryphal “there is a worldwide market for maybe 5 computers”.

Google: search, chrome, youtube

Microsoft: desktop software

Meta: social media

Maybe on some technical definitions of "monopoly" these aren't monopolies, but nothing remotely resembling a monopoly? come on maan

Google's Youtube unit is doing soft layoffs.

https://news.ycombinator.com/item?id=45766368

Yep. It would have to be something that dramatic to render all the technology and infrastructure OpenAI has obsolete. But if it's anything like massive data training on a huge number of GPUs then OpenAI is one of the winners.

I can't read your hyperbolically titled paywalled medium post, so idk if it has data I'm not aware of or is just rehashing the same stats about OpenAI & co currently losing money (mostly due to training and free users) but here's a non paywalled blog post that I personally found convincing: https://www.snellman.net/blog/archive/2025-06-02-llms-are-ch...

I'm waiting for my Google Glass smart glasses to be useful for anything other then annihilating the privacy of everyone around me

Blackberry was a big deal for a while, too

Also every one of them has hundreds of thousands of external contractors which are not reported anywhere.

And offshoring is also a huge cost-cutting effort everywhere.

What's shocking is the gulf between those companies and corporate 'normality'.

Eastern Airways, a UK airline, has just gone bust due to accumulated debts of £26 million. That's not even a rounding error for Google, yet was enough to put a 47-year-old company into bankruptcy and its staff out of work.

I think the only historical parallel to this disparity was the era of the East India Company.

The above article is not convincing at all.

Nothing on infra costs, hardware throughput + capacity (accounting for hidden tokens) & depreciation, just a blind faith that pricing by providers "covers all costs and more". Naive estimate of 1000 tokens per search using some simplistic queries, exactly the kind of usage you don't need or want an LLM for. LLMs excel in complex queries with complex and long output. Doesn't account at all for chain-of-thought (hidden tokens) that count as output tokens by the providers but are not present in the output (surprise).

Completely skips the fact the vast majority of paid LLM users use fixed subscription pricing precisely because the API pay-per-use version would be multiples more expensive and therefore not economical.

Moving on.

How about positive mindshare? Regular people not growing up absolutely hating nvidia's guts and only begrudgingly buying their products. Also ensuring that a pretty big industry won't die from becoming too expensive.

Plus, diversification is good for when the bubble inevitably bursts.

But that's long-term thinking and we can't have that. People give Huang credit for having had a long-term vision on AI, but it feels like he definitely has blinders on right now.

> as someone with no business experience, how they aren’t just pouring all of that money into enhancing their production capacity. That’s very clearly their bottleneck here.

They know this madness can't go on forever. The last thing they need is to be left with billions of dollars of unused capacity when the bottom falls out of this very stupid bubble.

The consumer gaming card market is minuscule in comparison to their primary market now, to the point where worrying about diversifying there probably doesn’t make sense. Nor does it really matter whether consumer gamers hate them. That is likely to have zero effect on their core customer now.

No-one "needs" or even wants appliances to be connected to the internet. You claim that "pretty much all" appliances are internet connected, while almost none of the appliances in my house are.

Underestimating compounding and secondary effects, especially while rationalizing the abandonment of their core market and capability is one of the most famous ways that big companies provide evidence of their downward spiral. I can feel the MBA energy from here.

Can you name any companies that suffered by switching focus away from one market where they dominate in order to also dominate a market that is 10x the size of the first market already, and growing faster?

If models are profitable once trained, isn't it weird that chatgpt and Claude have $200 tiers that still have usage limits?

>This is all dependent on token economics being or becoming profitable

What is the actual value of a token? If it were generated by a human expert in a given field? This should set an upper limit for now.

Every specific situation is different, but the pattern I mentioned is easy to find. Here are three examples: RCA, GE, HP.

> How about positive mindshare?

Does anyone who can afford an nvidia card actually buy something else? Yes some people hate nvidia, but it's not like they have a hard time selling cards.

> - Nvidia also benefits from growth due to the equity they own.

aka this might be nvidia's next pivot. Contrary to gaming cards, the AI GPUs are productive assets. If nvidia feels that they will be very productive, then it makes sense that they invest broadly in the companies that are likely to make these profits. To share in the rewards while selling more GPUs.

> They know this madness can't go on forever.

If they thought that, would they invest massively in the companies that own all these GPUs? They would not. They would invest in anything ELSE they could think of.

Consumers should already be glad that R&D for their products is being subsidized by OpenAI and Google

> Given how much click fraud there is [etc]

It's easy for the techies to see the problems. But advertising results have been very measurable for a very long time by now. Larger advertisers can leave the details to their techies and still be very clear as to their advertising's productivity post-cost of doing business.

I mean, who DOES need internet connected appliances? Are you implying these token-based techs will be shoved down our throats regardless of demand?

yes, these companies have a track record of disappearing profits :)

They have a track record of cornering a market and abusing their position, and also still somehow not being able to balance expenses and revenues to turn a profit that pleases shareholders. You get to decide if that's a problem with the company or the shareholders, I guess.

The equivalent of an additional $50 uber ride to the airport once a month can tank your business?

Monopolies being bad for free markets is a simplification. Substantial control over the market would be more accurate description of the issue.

But doing that would spook investors and possibly pop the bubble, so they look for ways to mitigate risk and fuel the bubble at the same time.

CUDA is where it is today because some years ago, people in grad school screwed around with CUDA on their personal gaming PCs