[N70Phone]

> 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.

[827a]

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.

[N70Phone]

> does work for Google and Meta

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.

[famouswaffles]

>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.

[N70Phone]

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.

[famouswaffles]

>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.

[N70Phone]

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.

[jsnell]

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.

[0] https://www.snellman.net/blog/archive/2025-06-02-llms-are-ch...