Leaked OpenAI financials show $38.5B loss and compute burn

That's not necessarily true.

It depends on two things that are impossible to derive from the leaked numbers:

1 - How much of their compute costs are subsidized.

2 - How much of that R&D chunk can actually be reduced for the company to continue working. What goes into "R&D"? Is that only things such as training for new models? This is impossible to determine from those numbers alone.

If those numbers are true, they would not be "close to profitability". They would be profitable, period.

This does not explain why they need to raise money like crazy. It would be possible to train new models at a more sustainable pace without the need to jack up prices at all, only with the difference in between "Revenue minus Cost of Revenue".

They also wouldn't need to be on a mad race to IPO and dump this into the public market.

To be frank, the more I look at those numbers, the more I think this is completely unsustainable.

They were first on a few things but the tell is the coherence of the thinking traces of Claude. You have to put a loss on that. GPT 5 series thinking traces are creepy, Gemini thinking traces are disturbing. They both represent forced discontinuities on the policy gradient.

Claude is good at tool use because it's gigantic and well-labeled, but the reason you pay the premium is for a thinking partner, not a tool user.

Claude Code is the cancer that will kill the patient, Boris is the the Kardashian version of Karpathy, with less business sense.

Except it's not true. No one lost $38.5B in a year just to 'hyper-grow' or whatever it means. Uber accumulated ~$30B loss over a decade.

Edit: I read it wrong. The loss was mostly caused by one-time event[0]:

> Before OpenAI’s switch late last year to become a public benefit corporation, investors in the company received convertible interest rights rather than conventional equity. Under US accounting rules, those interests were treated as liabilities and periodically revalued as the company’s valuation increased.

It looks like that OpenAI is actually quite in line with other companies that lost money to grow.

[0]: https://www.ft.com/content/e15b0d7e-ff6b-4f16-ba7a-4068feddb...

Growth means some inefficiencies, but their expenses are largely around commodities like electricity and data centers not a sudden army of salespeople. They also got 150M 11 years ago and 1 billion 7 year ago, they where quite large in 2022.

Basically you don’t get better at writing checks to your local utility which limits how much they can control costs.

That doesn't mean anything. There are examples to make both ways. E.g. WeWork

Look at how a utlity works, in setting price specifically, for things that are considered a public good. The story is not about how much profit or revenue they make. Its about how do you keep it afloat and expanding in the coming year. Thats it.

In the case of AI the marginal cost of the next token is not zero, and is in fact probably not going down much with volume, if at all.

So I'm not sure one can argue that scale will solve everything. It's very much like the old adage "we lose money on every sale, but make it up in volume".

No you don't.

They gave up on video because three separate Chinese companies were kicking their ass (and for cheaper).

Google has a better image model in the majority of cases. Much faster, too.

Claude Opus and Fable are like a billion times better. It's not even funny. Codex can't do Rust at all.

What does that leave them? Ads in ChatGPT? I've started to just rely on Google search blended with Gemini answers now because it's faster and doesn't spit out a 20-page essay of useless effusive prose.

Open source models will eat them from the bottom.

Will those enterprise contracts be renewed in a market full of alternatives?

There's nothing sticky about this company.

They're making a necklace with Jony Ive though, I guess?

There is something that has fundamentally changed (or broken, depending on your perspective) with the valuation of American tech companies. They've always traded at a premium, but the pandemic and the encroachment of the monopolists has turned the earth sour.

Similarly, SpaceX has already brought the cost of getting things to space down by a couple of orders of magnitude, and Starship is rapidly progressing with the potential to bring them down a couple more. The aspirational goals there are being able to get things to space on the order of $10-$20/kg. That would dramatically reshape not only space but even transport as we know it, very likely in a way analogous to how the ability to quickly send a 0 or 1 signal long distances for cheap reshaped the world in ways that would be essentially impossible to predict prior to its happening.

I'm bearish on the LLM revolution and bullish on the space one, which generally seems to also be the market consensus.

You can debate the assumptions, but it isn't witchcraft. The math is simple.

At least that's what I remember from the 00s.

That seems unlikely.

I think this is the key takeaway for the future of AI. Give tech a few years to catch up and we will likely have the functionally equivalent to today's models running on consumer grade hardware. From there it will explode, where "it" is how we use and interact with computers. AI will be integrated into just about every workflow.

The business case in this future would be to sell the trained models to end users. The investment would be shifted towards the training of models and delivering updates, with revenue coming from model licenses, upgrades and cloud services for tasks that exceed the local capabilities.

building a Rube Goldberg machine on Chinese models might work okay, but it will be brittle, and is unlikely to work as well as the latest and greatest model from OpenAI

the demand for intelligence is nearly limitless

UPDATE: Also bad news, you need to let go of all of sales and marketing and G&A. And THEN it's a 50% margin business.

Unless they increased their spending even more, "all they have to do" is cover 2025 with the 2026 revenue?

Huh? Where did $30 billion go?

It's not an issue if you're tracking the cash flow of the business or it's overall viability regardless of ownership structure. These book losses are just recognizing that the business has a higher market value so their ownership dilution commitments reduce the present value of the company more.

The big AI IPOs this year will mark the high point in the bubble IMO, with retail FOMO ensuring that they pop like SpaceX has.

After that I expect them to crater, just like all those Spacs and Blockchain startups.

> Revenue: $13.07 billion

> Cost of Revenue: $7.5 billion

In other words generating tokens is actually a profitable business even for the frontier models. It's best to IPO when it's the case.

[0]: https://www.ft.com/content/e15b0d7e-ff6b-4f16-ba7a-4068feddb... [1]: https://www.wheresyoured.at/exclusive-openai-financials/

I wish I could believe this but lighting giant stacks of cash on fire is, unfortunately, no longer a disqualifying event for tulip buyers.

I wouldn't bet they will have a successful IPO, but I also wouldn't bet they won't, it will be almost entirely vibes based at time of launch.

Given that, no, this question is still open.

and 7.81 billion in R&D from last year. I don't know how long it took to build the weights for the current model, or exactly how much that costs, but it's certainly more than zero days and zero dollars.

I also doubt that OpenAI could set that R&D expense to zero and survive without an agreement from Anthropic that they'll do the same... so that R&D expense can't be ignored when figuring up the total cost of the current model.

So I don’t see a company in immediate danger of collapsing, but I also don’t see a great investment at that valuation.

Just 10x your revenue without increasing R&D cost? where's this 1 magic trick and why can't every company just use it?

They would show a profit for 1 year and then become completely irrelevant.

The stock market has companies from massive to tiny. Each investor has the right to choose whether or not to invest in any one company. Some might be best served by investing only in profitable blue chips. For others, investing in IPOs is appropriate.

Your ire might be better directed at index companies who change seasoning rules right before a big IPO forcing unsuspecting investors to invest in unsuitable companies. And kudos to indexers like S&P who do not change the rules.

The other side of this are companies like Uber where (if we go by your logic), the public markets made a killing betting on a company that had massive losses. Should Uber also be blocked from an IPO even though objectively it turned out great?

Investing and markets will always decide between risk and reward. The risk of OpenAI is that it will never find profitablity but the potential rewards outweigh that in the current market perception.

In fact, the argument kind of shifts here, OpenAI can afford to IPO at this condition and still expect strong subscription precisely because its OpenAI. If it was some idk cooking appliance company with no exponential future payoff, the market would laugh and reject that IPO.

They can do that to OpenAI too but all signs say they wouldn't. You can still short the stock once it hits public if you really believe in the downfall of OAI in the future.

not sure where this constant dooming comes from

Pretty likely R&D, but obviously would need to be confirmed by OpenAI.

The original reporting includes this:

> The documents revealed how much OpenAI paid Microsoft for services. In the 2025 calendar year, OpenAI paid Microsoft $10.59 billion for “Research and development” expenses. We believe this most likely refers to the cost of training OpenAI’s models.

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

Given the enormous cost of training, would it be worth training new models then?

At that point however open weight model providers will start to shine. All eyes on China.

Can't really think of anything else he's been right about, though. I don't think "right" is what he's going for anyway, it's all about that validation and a coherent, testable hypothesis takes a very distant second place.

If this can be trusted, they are selling $1 for ~95 cents, and are spending $3 on R&D. This is... Not an unsustainable business model as long as the money keeps flowing.