Anthropic's IPO prospectus shows AI vision, surging costs
reuters.com
reuters.com
-LLMs profoundly change society -The LLM business is mangled in terms of ROIC vs CoC
Such a business already exists - airlines.
This nuance is what many here refuse/find difficult to understand.
The two things being true may as well be: LLM will not be transformative and the LLM business is mangled in terms of ROIC vs CoC.
In fact given the behavior of AI companies, I actually consider it more likely then not that the effects of the technology is severely over-hyped. I for one do not trust the words of the people who mangle their business in terms of ROIC and CoC. Why should I?
If this the criteria we are using form something being transformative, then being transformative is truly unremarkable in this context, to the point of being a distraction.
If LLMs are "transformative" in the same sense as counting "alchemy because of the scientific funding that went into various attempts led into many vital discoveries", what's going to be our version of "actually we can turn lead into gold now, we just have better things to do with the capability"?
Isn't it vibecoding? Turn out it's not really gold
We do have the means today to turn literal lead into literal gold.
The energy is better spent on almost anything else and the gold is radioactive afterwards, but we can do it.
The closest analogy I'd have for vibecoding is combustion engines. Historical antecedent was a toy, early industrial ones took a lot of fuel and were only useful to pump water out of the coal mines that supplied that fuel, but kept getting improved until they made a critical quality leap that took them from "slightly worse than a horse" to "marginally better than a horse" and then there were suddenly a lot of unemployed farriers.
But literal-lead-to-gold took a while longer than that, and a different set of inventions behind it.
The world looks pretty different today. Even if the model maker companies go out of business (I’m skeptical), the model weights would stick around (many are open freeware already).
I know many software engineers who haven’t written code this year. AI chatbots are regularly used as alternatives to searching manually by many people. Agents are becoming a valuable new enterprise tool, and now consumers tech consumers are hopping on board.
Even if you eliminate 100% of the people involved in creating software, that's still not enough money (and of course, that's not going to happen because someone has to know what to build).
Everyone is adding agents to enterprise stuff, but an overwhelming majority of the general population now hate AI for most things -- especially the "AI support" these companies are using. I think most people would rather suffer through overseas call centers with absolutely terrible representatives than deal with AI support (studies seem to indicate 80+% prefer a human to AI for support in general).
AI as a search engine is useful, but a very different animal. Proficient users want a way to check the AI like Google's AI search does (though the links sometimes don't agree with the summary), but these run very small models (8b or so) with the RAG backend doing the real work.
How many competitors does this space need? Companies can build their own proprietary RAG search engines, but users would almost always prefer the company make that public data available to Google and just use one well-optimized search engine instead of dozens of bad copies.
What about profitability? Google enshittified their search to increase retention and ad time, but AI search should reduce retention/ad time AND costs a lot more money to run too meaning it should lower their bottom line. If that weren't enough, their RAG system is almost certainly more replaceable by users with alternatives than their traditional search system. This seems like all downside for Google.
The currently well-served market for AI is not software engineering, it's approximately all of white-collar work, ranging from accounting and law, through medicine, general office work, to school administration, education, NGOs and governance.
Not everyone is going to just publicly brag about their AI use, but it's an open secret everyone is either using LLMs for half their work, or - if for some reason they're not busy enough to arrive at this idea on their own - under pressure to start using them.
The #1 and #2 apps are non-coding, pure consumer AI applications (Meta Muse and Momo).
How do you add them? Inside the model has tons of problems. From user context makes a bit more sense, but how do you decide and how do you ensure the context is actually beneficial for the company paying for the ads (advertisers are very sensitive about what content gets subconsciously associated with their brand).
How do you make sure a human sees them? This is a very hard problem even in normal ads and seems even more problematic with chatbots.
How do you attract advertiser dollars? Ad spending is zero-sum. You must somehow convince advertisers that your chatbot is a better ad platform than Youtube, Facebook, etc.
The only AI solution that seems reasonable is something like Google's AI search because the RAG backend ensures Google can control where ads show effectively through deterministic means (based on the websites it pulls). Google also has the ad network, consumer base, and provable humans to drive up ad value (this is without mentioning that Gemini falls behind on coding/math benchmarks, but seems to be better at "normie" interactions).
None of this helps any of the AI startups and running all this extra stuff for the same ad revenue cuts Google's profit margins too.
You're right. I didn't even need AI to get my point across.
I mean, if self education isn't a "real use", I wonder why all those libraries decided to dedicate all that shelf space to nonfiction books?
Wikipedia could probably save a lot of hard drive space too.
I'm by no means citing that AI is perfect, or that there are no problems or challenges ahead, but the self-lobotomizing AI doomerism/rejection is turning otherwise intelligent people into a horde of anti-AI lemmings that are afraid to apply the critical thinking they believe is being lost by AI users.
These things are puppeteering blender to model things for gods sake. Are you all blind?
Where? I can't find one company that did "AI layoffs" and their app/services got better. Give me just one good example please
Also computers. DEC and IBM and Gateway and whatever didn't extract the economic benefits of digitization. Even Apple extracts a vanishing fraction of the economic benefits the iPhone has created.
They try to get around this by charging you more after you've invested in your tools, but even then you can only go so far (though it's astonishing how far the big guys have managed to get regardless)
People seem to have forgotten the bust in railroads and Internet (etc), even though those technologies were transformative:
* https://en.wikipedia.org/wiki/Technological_Revolutions_and_...
One thing I'm wonder about: previous busts left useful infrastructure behind (rail, fibre) that could still be used. If/When the AI/LLM companies go bust, what will be left over afterwards and how useful will it be?
Many many idle GPUs.
I would bet that if all those GPUs go idle, they stay housed and cooled in the data center they were originally installed in, for better or for worse.
Yes, but what use will they have? Rail lines and dark fibre could be used post-bust (and don't depreciate all that quickly).
And that's at day 0. Because LLMs are not going away, thank to open weight models, and the race for capabilities has left so, so many low-hanging fruits unpicked, we'd have a decade or more of useful R&D to do even if LLM capabilities suddenly plateaued tomorrow and never improved.
I mean, look at Jev making round in the industry now - this is just a single example of a low-hanging fruit that took many years for someone to bother to pick up and market a bit. There's many, many more of these just laying around.
Don't focus on the hardware. The models themselves are tremendously valuable. These tools would've been considered alien technology just 15 years ago.
The numbers that Reuters describe in this article were entirely for 2025.
It's been well documented that Anthropic's revenue growth in 2026 has been enormous. This was the year of coding agents, and tokenmaxxing, and companies blowing enormous amounts of money on AI thanks to coding agent users spending hundreds (or thousands) of dollars a day.
Given that, I don't understand why the article and the headline are based exclusively on those 2025 numbers, with not so much as a hint to the reader that there are figures from the past 9 months that aren't covered by the documents Reuters saw.
Losing $8bn in 2025 isn't particularly notable if you've made ~10x that amount of revenue in 2026.
(How much did they lose in 2026? Wouldn't we love to know that!)
Is this just a thing with leaked IPO prospectuses and coverage of them?
1. Increased revenue normally means increased usage. [We don't dispute that, right?]
2. Increased usage normally means increased cost.
3. There is an exception to 2: if Anthropic made a gigantic discovery and was able to reduce the cost while increasing the usage - but since it would be in their best interests, they would announce this information and brag about it for months, but they haven't (what they do is just playing the quantization game all labs do, but this is beside the point).
4. Hence, we have very solid reasons to assume their costs increased.
"Opus 5.5 requires less compute to serve than Opus 5, and its pricing reflects that. Our tests show that at default settings it will cost 40% less than Opus 5 on typical workloads."
https://www.anthropic.com/claude-sonnet-5-5
"Sonnet 5.5 requires fewer tokens per task than Sonnet 5, so it’s less expensive to run. It also generates output 30%+ faster"
OpenAI have been achieving even more impressive optimizations, hence why GPT-6 Sol and GPT-6 Luna are half the price of their 5.6 equivalents.
>It's been well documented that Anthropic's revenue growth in 2026 has been enormous.
What Uber and other companies said is that the money they spent didn't generate the expected value they were promised. If it had generated $2 for every $1 spent, then Uber would be spending with no limits.
The lack of demonstrable return on investment means there is a ceiling to the market size, and profit is capped as cheaper models and self hosted open source models limit the amount flagship models can charge.
Long way to go till market saturation though so they will grow for foreseeable, but its a quandary of how much they spend on R&D vs giving future shareholders dividends.
Shouldn't they have set that per-employee budget to zero instead?
(I dug up the original source for that Uber doubts the ROI story a few months ago, it's a lot weaker than the headlines about it suggested: https://simonwillison.net/2026/May/27/product-market-fit/#th...)
For the AI companies to IPO at the money they want, they have to promise that they are going to be worth many multiples more of that value.
But currently they are spending hundreds of billions and despite this their models are not light years ahead of each other, or of the companies with much lower budgets and compute power.
What they claim they can offer in future profits is subject to considerable debate.
It's in the interests of VC's and their underlying rich investors to hype it ip, IPO and bank the cold hard cash.
Anthropic thinks it's worth more than insuring all US workers AND putting roof over their heads. AI sector thinks its worth magnitude more in aggregate. If they fully displace people, i.e. untied to headcount eventually then sure, but if not, based on what Uber pays, AI is basically worth as much as insurance.
Since then they've reported $65bn in annualized revenue by July: https://simonwillison.net/2026/Aug/23/anthropics-best-ai-mod...
And sure, they might be lying about those figures - but if they are, that's investor fraud, and they'll be in hot water with the SEC when they try to IPO. I don't think they are lying about the figures.
If I had numbers on their cost of revenue I would share those. As it stands I'm going to have to wait for either more leaks or their S-1.
By whom, exactly?
This isn't a standardized metric like GAAP revenue, and the company chooses how to compute it. Nothing stops them from taking a strong month (or week, or day, or hell even a second of revenue) and multiplying it out. It's also a different thing from booked revenue: the prospectus shows about $4.6B recognized in 2025, versus a ~$9B run rate at year-end.
Even taken at face value, it tells us nothing about costs. In 2025 they lost about $8B operating on $4.6B revenue, with compute alone at $7.3B. The $42B net loss is inflated by a ~$34B non-cash charge, so I'm ignoring that. The company says it hit positive adjusted operating income in Q2, but that's their own number, "adjusted" excludes whatever they choose such as training costs or the cost of staff, and we won't know the real picture until the full S-1 is public. Meanwhile they've disclosed $518B in future compute and infrastructure commitments against ~$20B in cash.
If they had a trillion dollars worth of revenue, it wouldn't mean jack shit if they had a trillion + 1 in losses.
I don't understand that argument.
If a company has a trillion dollars in revenue, even if they are losing money hand-over-fist, that still means they have convinced other companies to cough up a trillion dollars for what they are selling. That's a big deal!
The only case that isn't impressive is if they are literally selling dollar bills for 90 cents.
You can argue that Anthropic are subsidizing their tokens all you want, but since as a customer you can't just turn around and sell a token yourself for more than you paid for it that's still not a good argument for dismissing the amount people are willing to spend.
Most interesting: "Anthropic said nearly a quarter of its revenue came from two customers last year, and as part of its risk factors, warned that many of its largest clients were not locked into long-term contracts and could cut or stop spending."
- $42 billion net loss in 2025
- $518 billion in infrastructure obligations coming up (EDIT)
- 1/4 of revenue coming from 2 customers
Revenue growth means nothing if you don't have a viable business plan. Anthropic doesn't have one, except "this thing is more important than Big Bang". I don't discount the possibility that they stay afloat on borrowed money long enough to actually find a way to be profitable / rule the world. But it's nothing other than appeal to consequence right now.
"The near-$42 billion net loss included a roughly $34 billion accounting charge that reflected an increase in the estimated value of financing that could eventually turn into Anthropic shares, rather than money the company spent running its business."
As a member of the working class who believes this money is coming from systemic exploitation of the working classes, I hate it that Anthrhopic can just loose $8 billion like that. Those $8 billion could have been used elsewhere, including to mitigate the effects of the climate disaster, to educate the youth, towards social security, or to increase the wages of the working people who could have used it to pay rent, or go to the cinema, or a family trip to visit their grandma who lives in Wyoming.
8 billion is enough to give each of them $160. Great, all of Anthropic’s spending is enough to give each family a trip to Texas Roadhouse including dessert.
Have you ever been in poverty? I grew up that way and the then-equivalent of $230 would have meant not skipping Christmas when I was 6. It would have meant a full refrigerator, gas for the car for a couple of months, or so many other things.
https://www.sec.gov/Archives/edgar/data/1018724/000101872426...
Google, Amazon, Oracle, Microsoft, Meta, SpaceX, and tons of other startups are spending trillions on data centers, but everyone is renting them out. They aren't renting them to each other (and paying the extra overhead when they have their own servers).
That leaves basically just OpenAI and Anthropic on the hook to pay for everything BEFORE the GPU half of it depreciates away, but they are busy cutting prices to compete with Chinese models which runs counter to their need to increase prices to fulfill their obligations.
Keeping financiers of their IPO from understanding what they might be buying seems to swerve into fraud territory. Keeping their investors from knowing/understanding what the problems are also seems fraudulent.
I mean, sure, you think that and I know that many others do too.
It's Anthropic and OpenAI mainly competing for who gets used by the US government and possibly any US business that does any contracting work, while many others get banned. So basically, Fortune 500+.
There is also a non-zero possibility that the US Gov nationalizes the entire industry and then starts directly throwing Trillions USD into it in the name of "national security". Low % chance, but I can see it happening. Or at least the Fed Gov taking a controlling ownership stake.
It's also possible that the US Federal Government forces NVidia to outright prevent open models via: https://venturebeat.com/infrastructure/nvidias-openshell-con...
That spending obligation sounds extremely unlikely to be fulfilled without a bailout. Anthropic's IPO is them passing the hot potato forward.
Many of these obligations are with the big clouds who don’t have capacity to serve them anyways. Google has said they have hundreds of billions in purchase obligations they can’t fill because they don’t have enough TPUs and data centers. Google gets a bigger marketing and investor headline, and there’s a queue behind Anthropic if they bail, so of course everyone would sign the commitments knowing the risks.
I’m sure AWS and Azure are on the same page.
In the worst case, many of their biggest customers have tons of GPUs (Meta, AWS), so they could always license out their raw models at steep discount to help absolve themselves of the obligations.
Finally, in the worst case scenario, even with margin compression, they pre-purchased most of the compute so there’s not enough for the open models to run on. If Opus was the same price as Kimi/GLM, I doubt many people would pick the open models.
Amodei mentioned the reason for the big losses in an interview released on Feb 2026[1]. Assuming he was telling the truth, that's not a bad position to be in. From what I can tell from the replies to simonw, a lot of people are cynical about Anthropic's growth potential. I'd like to encourage the cynics to bet against Anthropic wish them luck. I will be doing the opposite.
Who are these two customers? A quick Google search seems to indicate that Cognizant is their largest "enterprise" customer by number of seats, Microsoft is their largest API customer, and the $10B contract they recently signed with Meta is their largest contract ever. But those metrics don't necessarily translate directly into annual revenue.
FYI. Not sure why everyone is fixating on the 2025 numbers without even bothering to look up the 2026 numbers…
What's in it for them?