Still, 700 million users, and they can still add a lot of products within ChatGPT. Ads will also be slapped on answers.
If all fails, Sam will start wearing "Occupy Jupiter" t-shirts.
They aren't pulling an Amazon snd balancing cash flow with costs. They're just incinerating money for a low value userbase. Even at FB arpu the economics are still very poor.
Okay, so still hundreds of millions of users
>They aren't pulling an Amazon snd balancing cash flow with costs.
Nobody said they were. I said having hundreds of millions of completely free users would suck the profitability of any business, and that the remedy would be simple, should the need for it arise.
>They're just incinerating money for a low value userbase.
If you don't see how implementing ads in a system designed for having natural conversations to users whose most common queries are for “Practical Guidance” and “Seeking Information” could be incredibly valuable then you have no foresight and I don't know what to tell you.
>Even at FB arpu the economics are still very poor.
No they aren't and I honestly have no idea what you're talking about. Inference is cheap and has been for some time.
Implementing adds is a hail-mary. It puts them in a knife fight with google which will likely result in a race to the bottom which OpenAI cannot sustain and win.
FB global ARPU is about 50 USD. At 700M customers, they do 35B in revenue annually. This compares to a publicly stated expected cost of approximately 150B in computing alone over the next 5 years (see: https://fortune.com/2025/09/06/openai-spending-outlook-115-b...). This leaves a profit of 5B per year, with 90B expected r&d costs. Even if OpenAI develops a product and fires all employees, you are looking at a ROIC of about 18 years.
Fundamentally, OpenAI does not have the unit economics of a traditional SaaS. "Hundreds of millions of users" is hundreds of millions of people consuming expenses and not generating sufficient revenue to justify the line of business as a going concern. This, coupled with declining enterprise AI adoption (https://www.apolloacademy.com/ai-adoption-rate-trending-down...) paints an ugly picture.
They are gaining everywhere. Some more than others, but to say they are only gaining in poorer markets is blatantly untrue.
>FB global ARPU is about 50 USD. At 700M customers, they do 35B in revenue annually.
Yeah, and that would make them healthily profitable.
>This compares to a publicly stated expected cost of approximately 150B in computing alone over the next 5 years
Yes, because they expect to serve hundreds of millions to potentially billions more users. 'This leaves a profit of 5B per year' makes some very bizarre assumptions. You’re conflating a future-scale spending projection with today’s economics. That number is a forward-looking projection tied to massive scale - it doesn’t prove current users alone justify that spend, and they clearly don't. There is no reality where they are spending that much if their userbase stalls at today's numbers, so it's just a moot point and '5B per year' a made up number.
>Fundamentally, OpenAI does not have the unit economics of a traditional SaaS.
Again, Everything points to their unit economics being perfectly fine.
- Prices of API access of Open models from third-party providers who would have no motive to subsidize inference
- Google says their median query is about as expensive as a google search
Thing is, what you're saying would have been true a few years ago. This would have all been intractable. But llm inference costs have quite literally been slashed several orders of magnitude in the last couple of years.
I've replied to you once man. Feel free to disengage but let's not act like this has been some ongoing debate. No need to make up stories.
Again, there are many indicators that inference per user is cheap. Even the sheer fact that Open AI closed 2024 serving hundreds of millions of users and lost 'only' 5B is a pretty big clue that inference is not that expensive.
Imagine 700M users “doomchatting” with GPT5 for several hours per day to justify the ROI of advertising.
Once OpenAI turns to ads, I think it's an indicator they are out of ideas.
Ads won't be slapped onto answers, my guess is that they will be subtly and silently inserted into them so that you don't even notice. It won't always be what you see either as companies, political groups, and others who seek to influence you will pay to have specific words/phrases omitted from answers as well.
AI at this point is little more than a toy that outright lies occasionally yet we're already seeing AI hurting people's ability to think, be creative, use critical thinking skills, and research independently.
Reddit.
And if someone is using an LLM for either topic, my sympathy goes out the window. Same as with reddit. E.g. if you take the discourse on /r/worldnews seriously, you deserve to be propagandized.
Business have higher friction - legal, integrations, access control, internal knowledge leaks (a document can be restricted access but result may leak into a more open query). Not to mention the typical general inertia. This friction works both ways.
Think capacitive vs induction electric circuits.
Similarly, if costs double (or worse, increase to a point to be close to typical SaaS margins) and LLMs lose their shine I dont think there will be friction on the way out. People (especially executives) will offer up ChatGPT as a sacrifice.
On the other hand, I remember when BlackBerry had enterprise locked down and got wiped out by consumer focused Apple.
In any event, having big consumer growth doesn't seem like a bad thing.
It will be bad if it starts a race to the bottom for ad driven offering though.
It’s the prodigal child of tech.
When OpenAI sells a ChatGPT subscription, they incur large costs just to serve the product, shrinking margins.
Big difference in unit economics, hence the quantization push.
It could indicate that many people find it more of an entertainment product than a tool, and those are often harder to monetize. You've got ads, and that's about it, and puts a probable cap on your monthly revenue per user that's less than most of the subscription prices these companies are trying to get (especially in non-USA countries).
(I find it way more of a tool and basically don't use it outside of work... but I see a LOT of AI pics and videos in discord and forums and such.)
Rest of the market be damned -- combined with the poor customer mix (low to middle income countries) this explains why there has been such a push by the big labs to attempt to quantize models and save costs. You effectively have highly paid engineers/scientists running computationally expensive models on some of the most expensive hardware on the market to serve instructions on how to do things to people in low income countries.
This doesn't sound good, even for ad-supported business models.
Is there enough product differentiation between OAI and Gemini? Not that I can see. And even if it was a low price, thats not the point - people hate paying a penny for something they expect to be free.
By the time OAI has developed anything that enables them to acquire and exercise market power (profitably), they will have ran out of funding (at least on favourable terms). Which could cause key talent to leave to competitors and so on. Essentially a downward spiral to death.
That said I do think eventually prices will increase somewhat, unless SOTA models start becoming profitable at current prices (my knowledge is at least 6 months old on this so maybe they have already become profitable?)
They only analyze the consumer plans, and ignored Enterprise, Teams and Education plans.
Wildly speculative predictions ahead, since obviously shifts can happen anywhere: The real change here is that the US was more a service economy while the world was exporting goods to it. But now with the 80% text use and jobs tanking and scams getting dramatically better and more powerful, it is possible the money generation shifts elsewhere. Language barriers are disappearing and individuals and teams anywhere on the planet can now use AI to extract money from wealthier counterparts including retirees, companies via employment, media, sales, companionship, extortions, you name it. If revenue and AI consumption increases from less than kosher sources over time, there is no incentive for AI companies to police it as much - money is money (unless government and AI companies blend in some way, but governments tend to prefer to harness rather than aid their constituents). There was a mention above about advertising always being an option, but convincing people to give you money by saying the right things would become a lot easier with AI than making and shipping products. So can learning how to make new things and inventing new tech. It all comes down to incentives and how much policing goes with the revenue demands.
people said same thing for youtube, "videos are bandwidth hungry", no way make money off of it.
consumer user is still feeding the LLM with training data.
Since many consumers are typically relatively tight-fisted in the b2c market, I don't think this bodes well for the long-term economics of the market. This may explain the relatively recent pivot to attempt to "discover" uses.
I don't think this ends happily.