Comment by byzantinegene
4 days ago
I believe they will last until they IPO, and not long after that. $200/mo plans are not good for their P&L when their users using $10000 worth api credits. That's -98% margin loss per user.
4 days ago
I believe they will last until they IPO, and not long after that. $200/mo plans are not good for their P&L when their users using $10000 worth api credits. That's -98% margin loss per user.
People point to the equivalent API costs to show that they are getting a great deal on the subscription, 10,000 dollars worth of tokens for 200 dollars. I do wonder if it's the other way around though - are the API users simply getting ripped off? I have seen Dario say in multiple interviews that they are profitable on inference, which maybe he was only meaning to refer to API usage, but that's not the impression I got.
It's not a 98% margin loss if your users are unwilling to pay 50 times the cost that they were previously paying, and if they have other options like open source providers. The calculus isn't so simple because some portion of users would switch to API, and so it's about how many would continue using the service rather than leaving for a competitor.
I'm aware they need to recoup the enormous cost of training and data centers, but on a purely inference cost level I'm not convinced that the 200 dollar plans are unprofitable.
> I'm not convinced that the 200 dollar plans are unprofitable.
Especially considering not everyone is tokenmaxxing, and in most parts of the world people take leave and companies do not cut their subscriptions.
I suspect they are priced to have a lifetime average price/token amount that is roughly break-even, or maybe a slight loss leader.
> have seen Dario say in multiple interviews that they are profitable on inference, which maybe he was only meaning to refer to API usage, but that's not the impression I got.
I think he does mean API usage. Don't forget they can (and do) adjust the number of tokens you get on each plan at any time to adjust their margins on those.
That means he knows that is controllable, and it only the underlaying inference that defines the succes or otherwise of the company.
> Especially considering not everyone is tokenmaxxing
Exactly. I have the Claude $100/mo plan, and use it moderately for open source hobby stuff. I still haven't dipped my toes into the Fable pool, but I always use Opus 4.8 on xhigh, and I never hit my limits.
On the other hand, though, there have been times when I've looked at /usage for a long-running session (e.g., 7-10 days, after it's compacted a few times), and it showed I'd used ~$450 worth of tokens just for that session. So I'm clearly getting value for the money here when it comes to the subscription cost. But I still don't hit limits, so...
Yea, it’s like pointing at the cost of renting all individual movies and TV-series at Netflix and concluding that Netflix subsidizes the subscription with tens of thousands of dollars.
I figured the subsidization is to entice people to give training data.
Are your thought patterns worth 9800 dollars a month?
What's the RoR on analyzing those thought patterns?
I simply do not believe the switching costs are high enough that they could eliminate those plans. The Chinese models will eat their lunch.
Open weight models are catching up, and I see no reason to think this will change. That will largely define the economics of this industry. It seems highly improbable that there will be people spending thousands on API credits will be a thing in the future.
No way in hell are the majority of Claude Code users burning 10k worth of credits. Many of them probably barely use it. There'll be a bell curve, and we have no idea what it looks like.
They don't need to be the majority. One big company paying 200/300k in credits each month easily makes up for the majority of single users not doing so. I believe AI companies today make money through b2b enterprise deals and not selling to individual users, the latter is mostly a marketing expense to get people to use their product instead than the competitors one.