> the industry is spending over $30 billion a month (approximately $400 billion for 2025) and only receiving a bit more than a billion a month back in revenue.
I suspect that this revenue number is a vast underestimation, even today, ignoring the reality of untapped revenue streams like ChatGPT's 800M advertising eyeballs.
1. Google has stated that Gemini is processing 1.3 quadrillion tokens per month. Its hard to convert this into raw revenue; its spread across different models, much of it is likely internal usage, or usage more tied to a workspace subscription rather than per-token API billing. But to give a sense of this scale, this is what that annualized revenue looks like priced at per-token API pricing for their different models, assuming a 50/50 input/output: Gemini 2.5 Flash Lite: ~$9B/year, Gemini 2.5 Flash: ~$22.8B/year, Gemini 2.5 Pro: ~$110B/year.
2. ChatGPT has 800M weekly active users. If 10% of these users are on the paid plan, this is $19.2B/year. Adjust this value depending on what percentage of users you believe pay for ChatGPT. Sam has announced that they're processing 6B API tokens per minute, which, again depending on the model, puts their annualized API revenue between $1B-$31B.
3. Anthropic has directly stated that their annualized revenue, as of August, was $5B [2]. Given their growth, and the success of Claude 4.5, its likely this number is more around $6B-$7B right now.
So, just with these three companies, which are the three biggest involved in infrastructure rollouts, we're likely somewhere in the realm of ~$30B/year? Very fuzzy and hard, but at the very least I think its weird to guess that the number is closer to like $12B. Its possible the article is basing its estimates on numbers from earlier in 2025, but to be frank: If you're not refreshing your knowledge on this stuff every week, you're out of date. Its moving so fast.
> 2. ChatGPT has 800M weekly active users. If 10% of these users are on the paid plan, this is $19.2B/year. Adjust this value depending on what percentage of users you believe pay for ChatGPT. Sam has announced that they're processing 6B API tokens per minute, which, again depending on the model, puts their annualized API revenue between $1B-$31B.
OpenAI announced a few months ago that it had finally cracked $1B in monthly revenue (intriguingly, it did so twice, which makes me wonder how much fibbing there is in these statements).
I'll also say this: the fact that AI companies prefer to tout their usage numbers rather than their revenue numbers is a sign that their revenue numbers isn't stellar (especially given that several of the Big Tech companies have stopped reporting AI revenue as separate call-outs).
> OpenAI announced a few months ago that it had finally cracked $1B in monthly revenue (intriguingly, it did so twice, which makes me wonder how much fibbing there is in these statements).
I believe this is incorrect; as far as I've heard, an anonymous source leaked that OpenAI had hit $12B in annualized revenue a few months ago [1]. I do not personally put any weight in leaks, and prefer to operate on data that has been officially announced.
"Reported to shareholders" is a whole heck of a lot more accurate than some person on the internet playing numerology to turn similarly sketchily-sourced user numbers into revenue numbers.
That number was not reported as "reported to shareholders". Again, its astounding how wrong you keep getting this. It was leaked to The Information by an anonymous source who claimed to be a shareholder who received this financial disclosure.
Its all about citation. Everyone who read my numerology estimations above knew that they were estimations. You, on the other hand, lied about two different leaks of OpenAI's revenue numbers as being "official".
I think you're underestimating how quickly users can move to another platform if something better / cheaper shows up unless there are user network effects that benefit / keep people on a platform. We've lived through several of these - yahoo/lycos to Google. A bunch of terrible providers to GMail, various messengers to Apple/WhatsApp/line dominating countries etc. This space seems ripe for the second mover advantage effect
Yes, I moved from Yahoo to Google in multiple apps. And yet, once I subscribed to ChatGPT, it satisfies what I need, despite all the noise I hear about the alternatives.
> even today, ignoring the reality of untapped revenue streams like ChatGPT's 800M advertising eyeballs.
Respectfully, the idea of sticking ads in LLMs is just copium. It's never going to work.
LLMs' unfixable inclination for hallucinations makes this an infinite lawsuit machine. Either the regulators will tear OpenAI to shreds over it, or the advertisers seeing their trademarks hijacked by scammers will do it in their stead. LLMs just cannot be controlled enough for this idea to make sense, even with RAG.
And if we step away from the idea of putting ads in the LLM response, we're left with "stick a banner ad on chatgpt dot com". The exact same scheme as the Dotcom Bubble. Worked real well that time, I hear. "Stick a banner ad on it" was a shit idea in 2000. It's not going to bail out AI in 2025.
The original content that LLMs paraphrase is itself struggling to support itself on ads. The idea that you can steal all those impressions through a service that is orders and orders of magnitude more expensive and somehow turn a profit on those very same ads is ludicrous.
While it didn't work in 2000, "just stick ads on it" does work for Google and Meta, driving over $400B in combined annual advertising revenue. Their model, today, is far more relevant than calling back to antiquated banner advertising models from 25 years ago; you'll have to convince me that Google and Meta's model cannot work for OpenAI, which you have not adequately done.
I will point out that this is contentious, both of these companies are subject to regulatory investigations around their monopolistic practices & the matter that they are pretty much the only companies for which this is profitable.
> Their model, today, is far more relevant than calling back to antiquated banner advertising models from 25 years ago
Hardly. It's fundamentally the same model; Content with an advertisement next to it. Whether that is a literal banner ad or a disguised search result, none of the formfactors are new.
For all the advances in ad-tech, CPMs are still the same old dogshit they were shortly after the dotcom bubble, looking better only because of inflation.
> you'll have to convince me that Google and Meta's model cannot work for OpenAI, which you have not adequately done.
That's the "orders and orders of magnitude more expensive" part. Neither Google Search nor Facebook are that profitable per single ad, they make it up in volume. LLMs are simply more expensive to operate than a search engine or a glorified web forum. Can OpenAI cut down their opex and amortized-cap costs down to less than the half-penny they'd extract with good CPMs? Probably not.
But there's a deeper layer. The "fund AI with ads" model paints a scenario in which OpenAI would have to overtake Google; They need the ad-tech monopoly to push up CPMs or you can cut that half-penny down an order of magnitude.
This is unlikely. To make ChatGPT work as a search engine requires all the infrastructure of a search engine. Ipso-facto they are always more expensive than a standalone search engine.
Yet at the same time, people only care about ChatGPT as search because Google Search is shit now. Were ChatGPT to ever become a serious threat to Google, Google can simply turn off the search-enshittifier for a bit and wipe out ChatGPT's marketshare, and push them into bankruptcy by drawing down CPMs below OpenAI's sustainability level.
>That's the "orders and orders of magnitude more expensive" part.
It's not orders of magnitudes more expensive and if we take the most recent report for the half year, then they need a per quarter ARPU of $8 for their free users to be profitable with billions to spare. That is low. This is not some herculean task. They don't need to 'overtake google' or whatever. They literally don't need to change anything.
You can't average out the userbase like that because the individual usage of the service varies wildly, and advertising revenue is directly tied to amount of usage.
Especially because OpenAI highly inflates user figures.
> It's not orders of magnitudes more expensive
This too is skewed by averaging with users who barely use the service.
>You can't average out the userbase like that because the individual usage of the service varies wildly
Yes you can. This is how Meta, Google et al report their numbers. Obviously I'm not expecting each user to bring in exactly $8. The point is that the value they need to extract from their free users to be profitable is very small and very achievable. You and many people here have completely incorrect notions on how expensive inference is. Inference is cheap, and has been for some time now.
>and advertising revenue is directly tied to amount of usage.
Open AI with 800M weekly active users processes 2.6B messages per day. Google with ~5 billion users processes ~14 billion searches per day.
>This too is skewed by averaging with users who barely use the service.
No it's not. Inference is just not that expensive. Model costs have literally crashed several orders of magnitudes in the last few years. Sure, in 2020, this would be a very serious concern. In 2025, it just isn't.
My point is that for these purposes, users are not fungible. You can't just divide the cost-revenue equation by the amount of users N on both sides.
> No it's not.
If you add a pile of fictious users to the usercount, the apparent average cost-per-user drops as the fictious users do not use the service and do not add their own costs. This lowers the apparent amount of per-user revenue you need.
However, as fictious users also do not generate revenue, this is all smoke and mirrors.
>My point is that for these purposes, users are not fungible. You can't just divide the cost-revenue equation by the amount of users N on both sides.
Again, yes you can if you're simply trying to see the relative level of value you need to extract from your users. It's not a complicated idea. $8 is well below what Google, Meta report. You were wrong. They don't need to reach a high bar. End of story.
>If you add a pile of fictious users to the usercount, the apparent average cost-per-user drops as the fictious users do not use the service and do not add their own costs. This lowers the apparent amount of per-user revenue you need.
As always, nonsensical hypotheticals are just that. Nonsensical.
Not only can the users you're talking about not exist in reality, the numbers being thrown around are literally based on their Weekly active users.
There are multiple ways to do the computation. All of them will show LLMs having unit economics that are at least an order of magnitude better than search engines for the search engine use case[0]. Not multiple orders of magnitude worse like you claim. You're off by at least three orders of magnitude.
Ad-supported LLM Chatbots will be one of the most lucrative businesses ever.
I suspect that this revenue number is a vast underestimation, even today, ignoring the reality of untapped revenue streams like ChatGPT's 800M advertising eyeballs.
1. Google has stated that Gemini is processing 1.3 quadrillion tokens per month. Its hard to convert this into raw revenue; its spread across different models, much of it is likely internal usage, or usage more tied to a workspace subscription rather than per-token API billing. But to give a sense of this scale, this is what that annualized revenue looks like priced at per-token API pricing for their different models, assuming a 50/50 input/output: Gemini 2.5 Flash Lite: ~$9B/year, Gemini 2.5 Flash: ~$22.8B/year, Gemini 2.5 Pro: ~$110B/year.
2. ChatGPT has 800M weekly active users. If 10% of these users are on the paid plan, this is $19.2B/year. Adjust this value depending on what percentage of users you believe pay for ChatGPT. Sam has announced that they're processing 6B API tokens per minute, which, again depending on the model, puts their annualized API revenue between $1B-$31B.
3. Anthropic has directly stated that their annualized revenue, as of August, was $5B [2]. Given their growth, and the success of Claude 4.5, its likely this number is more around $6B-$7B right now.
So, just with these three companies, which are the three biggest involved in infrastructure rollouts, we're likely somewhere in the realm of ~$30B/year? Very fuzzy and hard, but at the very least I think its weird to guess that the number is closer to like $12B. Its possible the article is basing its estimates on numbers from earlier in 2025, but to be frank: If you're not refreshing your knowledge on this stuff every week, you're out of date. Its moving so fast.
[1] https://www.reddit.com/r/Bard/comments/1o3ex1v/gemini_is_pro...
[2] https://www.anthropic.com/news/anthropic-raises-series-f-at-...