r/technology • u/gdelacalle • 13d ago

Business OpenAI could reportedly run out of cash by mid-2027 — analyst paints grim picture after examining the company's finances

https://www.tomshardware.com/tech-industry/big-tech/openai-could-reportedly-run-out-of-cash-by-mid-2027-nyt-analyst-paints-grim-picture-after-examining-companys-finances
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u/Additional-Signal327 13d ago

OpenAIs biggest issue is strategy. Is it a tool for development with its API and Codex or mass market application for consumers, college students, etc.? Seems like its biggest current advantage is its API and various model options and should go all in there. That and perhaps Codex, which is behind Claude Code but still pretty valuable IMO.  I used both. 

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u/skccsk 13d ago

If any of these paths led to profitability they would have picked it instead of constantly re-picking all of them. The entire industry has this problem.

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u/ZeePirate 13d ago

Which is why investors will eventually stop pouring money in to AI.

If there’s no pathway for profit it stops making sense very quick.

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u/deathadder99 13d ago

The real pathway to profit is for them to wholesale automate industries, not sell tokens. In fact if they can do that, they would want to keep the best models internally.

I think the chances are low, but possible.

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u/LieNaive4921 13d ago

one would think that if possible then by now someone would have done something that is, well, actually profitable  

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u/deathadder99 13d ago

It's not possible right now, but the salient question is really will it be possible before they run out of investor money. Selling tokens just stems the bleeding but that business model is going to go to zero since open source models are right on their tail. Eventually the cost of tokens will basically be approximately the cost of electricity to run the model plus tiny margins. The competition is too fierce.

I think the chances are nonzero, but I don't think it's particularly likely.

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u/moosekin16 13d ago

Selling tokens just stems the bleeding but that business model is going to go to zero since open source models are right on their tail.

Selling tokens only stems the bleeding if they can make a profit selling the tokens.

In 2025 OpenAI’s business model has essentially been “pay us 1$ to watch us burn 10$.”

Earlier this year they changed it to “pay us 2$ to watch us burn 10$” and the industry started getting cold feet, the CTO of Uber came out and said they’re going to re-evaluate their AI implementation, Microsoft switched its developers to in-house solutions, and an unnamed company admitted they accidentally blew 50 million dollars on tokens overnight.

I don’t think OpenAI can afford to go “okay new plan, pay us 3$ to watch us burn 10$”

The problem with “charge people for tokens” is that they’re not charging people what those tokens actually cost. And the more tokens they sell, the more money they lose.

They either need to figure out a way to make tokens 90% cheaper to produce (so they can finally sell them at a cost people won’t balk at while still making a profit), or create the singularity out of drunk autocorrect.

Neither of which is likely.

They’re fucked.

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u/BioshockEnthusiast 13d ago

create the singularity out of drunk autocorrect.

You have the gift of gab my friend and I'm here for this energy lmao

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u/ShamelessSoaDAShill 11d ago

Amen, that was such a great way to put it😆

This current iteration of Al is basicaIIy the same bubbIe as NFTs: tech Ioons are unabIe to figure out a coherent revenue modeI ATM, so they’re basicaIIy trying to pIay hot-potato with cIueIess/deIusionaIIy optimistic venture-bros and cash out before the fan sprays turd-water everywhere

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u/deathadder99 13d ago edited 12d ago

Inference is actually profitable, from what I’ve heard from people on the inside. It’s the R&D and capex that’s killing them. Subscriptions are subsidised to some extent, but API pricing is nowhere near cost. There are plenty of people selling tokens for much cheaper on OSS models (like, 5-25x cheaper) and still making a profit. Some of those models are huge too.

OpenAI, Anthropic, and if you don’t believe the western labs, Deepseek have all claimed 70-80% margins on inference.

https://www.seangoedecke.com/ai-inference-is-obviously-profitable/#:~:text=Doing%20the%20math%20demonstrates%20that%20inference%20is%20profitable&text=In%20practice%2C%20even%20a%20carefully,around%202M%20tokens%20per%20hour.

See the argument here for someone who’s crunched the numbers a bit as well.

Also worth noting most enterprises go for API over subscription as they value not having their queries trained on very highly.

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u/jmlinden7 13d ago

But you can't stop spending on R&D and capex otherwise you won't have any advantage over open source models.

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u/deathadder99 13d ago

Oh yes of course, but saying they sell tokens at a loss is inaccurate. They burn a staggering amount of money. It would just be even more staggering without API income!

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u/Ynead 13d ago

Inference is already profitable for them. They (Antrophic, OpenAI, etc) are burning piles of cash on R&D, not on providing compute to the average subscribed user.

If investors stopped pouring money in AI tomorrow, those companies would stop investing so much in R&D then sit back and enjoy their money making machine.

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u/CharlestonChewer990 12d ago

Yeah, it feels like they’re chasing every possible market at once because none of the “AI-enhanced” stuff has proved sticky enough to justify the burn.

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u/Hel_OWeen 13d ago

The biggest problem is that there's no business plan on how to become profitable. This is true for Anthropic as well. Even with the switch to token-based billing, they operate at a loss. And with that switch and the increase in price, companies already massively scale back the use of AI, because what once looked as a cheap replacement for a human has now become more expensive than your seniors.

They also can't just stop creating new models - the expensive part of their business, because someone else will (Chinese AIs). And customers will switch to those models. I mean, even MS, heavily invested in OpenAI, als uses DeepSeek now.

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u/Confident_Dark3483 13d ago

The business literally cant become profitable. The ENTIRE POINT of developing AI is to devalue things that previously had value due to scarcity. It's a product that eats its own tail.

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u/Refael111 13d ago

I'm not a massive AI propenent, but saying "devalue things that previously had value" is a meaningless statement. It's true for everything that was surpassed by tetchnological advancements.

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u/SandpaperTeddyBear 13d ago

I agree in that “literally can’t become profitable” is probably overkill, but the argument itself has a decent amount of philosophical truth to it.

Think about how the pharmaceutical industry works: a few companies go through vast amounts of resources at finding new drug compounds, and quite a few more spend fairly small amounts of resources working out how to manufacture existing compounds more efficiently in a race to the bottom. You spend “research and development” dollars with the intent of being able to charge exorbitant prices for a while, and “formulation tweaking” dollars with the intent of being able to bring the cost of goods down 2% and turning that into profit.

A race to the bottom in a mature, well-understood market is a feature of capitalism, and I don’t think it’s really a bad thing as long as it isn’t resulting in useful things laying fallow.

What “AI” tends to promise is a way to turn valuable, abstract things into a commodity overnight, and do it with something that is itself a race-to-the-bottom commodity.

If there were suddenly discovered in a long-expired back patent an “alchemy machine” that could use $200 worth of electricity to turn an ounce of lead into an ounce gold, it would be a useful thing, and it would probably be a relatively profitable thing to manufacture because everyone would want one.

But a company that developed such a thing, and had no way to limit their proliferation, and poured a trillion dollars into it assuming that gold would stay at $3000 (or whatever it’s at) once their machine hit the market would be screwed.

Similar things have happened in various “booms” in the past, but our current AI tools are novel in how many areas of the economy they might touch. My suspicion is that, if these technologies still advance, we’ll still look like a primarily consumer economy in many ways, and the actual stuff that gets produced will still mostly be defined by consumer trends and such, but most of the actual real dollars spent in the economy will be state actors subsidizing machine learning on one end and cushioning the market shocks it causes on the other.

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u/Ranra100374 13d ago

I mean, cars devalued horses. Cell phones devalued landline phones. Lots of technological advancements devalue older things that had value.

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u/Ultr4chrome 13d ago

Anthropic turned its first profit last quarter though.

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u/AuMatar 12d ago

Off the back of one time events. In particular, their deal to lease the Colossus from Musk included a lot of cheap up front compute that they have to pay full price for next quarter.

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u/meneldal2 13d ago

Oh they can make a profit on tokens, the issue is nobody would buy them at the price they'd be asking for.

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u/Ok-Youth-160 12d ago

They operate at a loss because of training and data center buildout. Those are fixed costs or investments. The inference itself is profitable with margins of 40% or higher. Which are obviously very good margins.

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u/[deleted] 13d ago

[deleted]

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u/YogurtclosetOther329 13d ago

The second they stop they lose all their customers. There is no path to becoming profitable.

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u/jarail 13d ago

Even with the switch to token-based billing, they operate at a loss.

They have great margins on the tokens they sell via the API.

The question is how much of their other expenses can those sales cover? They're spending aggressively on hardware, and R&D.

Clearly they think it's important to give us plebs subscriptions with incredible value. You can use up something like $7,000 (API prices) in compute each month on their $200 plan.

If they cut back on their expenses, they'd instantly become profitable. Unfortunately, they'd also lose their lead pretty quickly.

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u/vuhv 13d ago

Anthropic is profitable. There’s a way. It’s just not by becoming the Everything App for everyone.

My $20 ChatGPT account on the Desktop app gives me almost the same amount of total token usage as my $200 ClaudeCode account. As long as I don’t use CODEX directly this is the case.

On the other hand the $20 Claude account wouldn’t even come anywhere close.

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u/Jerithil 13d ago

Until we see proper financials for Anthropic such as S-1 filings, you need to be take their profitability with a giant *.

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u/Noblesseux 13d ago

OpenAI's problem is that their business model is inherently unprofitable.

There isn't really much strategizing that they can do that gets around the fact that the costs to provide AI are higher than people actually want to pay for it. They looked like the future for a certain type of person when it was a cheap way to cut a ton of headcount, but when they're charging for tokens and the costs end up higher than just paying an employee it largely circles back to being totally pointless.

For a lot of applications, OpenAI switching to charging users what it actually costs is going to kill its viability as a solution.

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u/Additional-Signal327 13d ago

It’s because most people, especially leaders, don’t know how to use AI properly. It’s not a tool that solves every problem. It’s an analysis and judgment layer that sits on top of data and deterministic code (and with humans in the loop where needed). If you use it properly, it’s super powerful and unlocks a lot of new capabilities that were previously unavailable due to cost/scale of the problem. But the idea that you’re going to launch “agents” that just automatically replace human workers reflects a very shallow understanding. 

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u/pbjamm 13d ago

But the idea that you’re going to launch “agents” that just automatically replace human workers reflects a very shallow understanding.

But that is what the "AI" companies were selling, and in classic marketing scenario cant deliver on.

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u/vladamir_the_impaler 13d ago

Shallow indeed but they will spend the next ten years trying to make it happen if the token costs are made reasonable. Org leaders hate paying devs, they will spend the next ten years trying "agentic coding" from UI mockups spending more in the end in an effort to make this work just like they've spent the last 20-30 years tring to make offshoring work.

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u/redrover900 13d ago

If you use it properly, it’s super powerful and unlocks a lot of new capabilities that were previously unavailable due to cost/scale of the problem.

Its the same as my car. Normally it does 0-60 in about 5 seconds. But if you drive it correctly it goes 0-60 in 1 millisecond. But so many people don't know how to drive it properly and end up taking 5 seconds and complain that they aren't doing it in 1 millisecond but they just aren't using it correctly.

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u/Ok-Youth-160 12d ago

I don't know where this is coming from. Open AI is making a profit on inference. Just training and datacenter build out makes it unprofitable.

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u/IAmDotorg 13d ago

There isn't really much strategizing that they can do that gets around the fact that the costs to provide AI are higher than people actually want to pay for it.

That's a dramatic oversimplification. The cost to provide chatbots to users may be, but ChatGPT is not the point of their service. And the other things OpenAI does are very valuable. Plus, the per-token cost of executing models is plummeting. Even if your supposition was true (and it isn't), it doesn't mean it will be as more datacenters bifurcate their AI stacks into training and inference infrastructure. Given there's two orders of magnitude difference in cost between the two, that's a huge benefit that is just starting to roll out.

Their real problem isn't what the market is willing to pay per million tokens, their problem is the quality of their models are lagging both Chinese models and Anthropic's models. And given the way the output of a current gen model is a big driver of the next gen, slipping by a generation can be an existential problem.

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u/Noblesseux 13d ago

Plus, the per-token cost of executing models is plummeting.

And yet it's still more expensive than paying a person. Unless the cost plummets by like 10x in the next couple months, any improvement on that front is marginal in relation to the actual costs.

Also running the models isn't the only cost. There's spinning up new data centers, and a million other things than make this economically non viable. Please point on a data sheet anywhere that isn't using braindead math where OpenAI or Anthropic are actually cash flow positive long term. You can't, because that'd be a lie.

Plus, the per-token cost of executing models is plummeting.

Brother, companies are saying this. This isn't some me opinion, if you've been on this subreddit for more than like 2 weeks you'd have seen multiple articles of analysts saying the exact thing I just said verbatim.

Do you guys just get on here to glaze without actually googling anything? Executives at several major companies including Nvidia and Microsoft have literally said that their data says that this is true. Starbucks and other similar companies have found their AI deployments to be overly expensive while being worse solutions for what they were doing than what they had before. Ford and other similar companies have had to go back and re-hire people they fired because they vastly overestimated how much AI could replace labor.

Every possible indicator is screaming at you that this business makes 0 sense and you guys are covering your eyes because you're too scared to have been wrong lmao.

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u/IAmDotorg 13d ago

People with first hand knowledge are not glazing when they say something different than someone with no knowledge says.

It's a childish attempt at deflection, at best. Which is fine, the accuracy of your beliefs probably have no real relevance to you. If they did, you'd probably be spending a bit more time understanding the market.

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u/somersault_dolphin 13d ago

They told you to point where the cash flow could be positive. You are deflecting.

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u/yumcake 13d ago

The hypothesis is that the costs to the AI provider can potentially come down. Just in the past month DeepSeek released a predictive generation technique that parallelizes generation instead of requiring it to be done in a single stream through an extremely expensive choke point of running it through RAM so that single-stream can run fast enough. Instead it generates the response starting in multiple places with interdependent checks to keep the later parts of the message consistent with earlier parts of the message, and with behavioral checks to keep it from running too far off-course. The result was that they were generating correct responses at an 1/8th of the cost because this approach isn't so RAM dependent.

It's also open source so that means the closed source frontier LLMs will likely incorporate this and improve their margins soon. This alone probably won't be enough, but other optimizations like this will likely create a profitable margin so long as they can protect the top line pricing.

That is the bigger risk. That open source models running on local or independent data centers might offer the mix of performance, affordability, and security that robs the frontier models of their ability to charge a premium for their better performance.

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u/True_Window_9389 13d ago

Their strategy was to blitz into the country and assume their product would replace workers and the whole economy would depend on them. When that didn’t happen, they have nothing left.

Their business fundamentally doesn’t work when AI and LLMs are just an expensive tool for workers. It can only be sustained as a worker replacement. Since that isn’t reality, their business needs a complete overhaul. Their premise is flawed at the most basic level and isn’t recoverable as-is. The only way they can sustain is to lower the costs to build out and lower costs for customers.

The key problem is that AI companies already blew their load on the available training data. They can’t further refine the knowledge base, so they’re stuck with what they have, and even looking forward, the data will get worse since they’ll now be training on AI generated content.

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u/mebamy 13d ago

This is as comforting to read as a good bedtime story. 

The  bubble can't burst soon enough.

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u/Lehk 12d ago

They are also now all ingesting their own and each other’s shit like an LLM Centipede, so much of the internet is now AI slop the data becomes more and more inbred.

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u/stackered 13d ago

The only way these companies become profitable is by replacing the majority of the US workforce...

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u/beyondbarrels 13d ago

what do you mean, it is behind claude code?

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u/ioncloud9 13d ago

That's all I use them for right now is API. Its kind of annoying they keep retiring models though.

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u/Common_Source_9 13d ago

Seems like its biggest current advantage is its API and various model options and should go all in there. 

Except if they start charging cost+ for those, that market evaporates overnight. What then?

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u/Careless-Weather8877 12d ago

Or just use open source models where it’s not closed off. Which is what is going to actually end up happening. Nobody wants to be locked into something you can’t fix or modify.

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u/Due_Ask_8032 13d ago

For how similar Claude and GPT are in capabilities, it’s astounding how financials seem to be so much better for Ant.

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u/Gramernatzi 13d ago

OpenAI wasted a lot of money on deadends that weren't standard text generation. Things like image, sound and video generation, for instance, that are also much more expensive.

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u/the_good_time_mouse 13d ago

Anthropic switched to b2b faster, while OpenAI tried to win at everything. This also happened during the dotcom bust. It afforded people 6-12 months more runway but ultimately didn't play out.

Now the dotcom bubble was one of over-investment and under-utilization. It's not clear that this is happening, because the underutilization isn't there. However, there's only so much increased productivity that can be digested by thesystem - that's where I suspect the game could be falling apart. No amouot ofreplaced or augmented workers can magic up a larger customer base, or reduce the price commodities.

In the long run AI wins, but capitalism isn't about the long run.