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by aspenmartin 29 days ago
He's saying he's getting a great deal...a token from Opus on Claude code is the same as a token from Opus on the API. I remain as confused as Simon. He's not talking about "here's the ROI I got from my $100 subscription" it's "here's how much I saved from getting the monthly subscription instead of sending things through an API".
2 comments
mjr00 29 days ago
Right, the confusion is that the quote-unquote "subsidized" monthly pricing is often used by Anthropic/OpenAI skeptics as proof that inference is unprofitable, i.e. the API would have cost $2000 but you only paid $200 for a subscription, therefore OpenAI is selling dollars for 95 cents and the house of cards is about to collapse. As the GP says, this is faulty logic because we don't know what the actual cost of a token is; OpenAI might only pay $1 in inference costs, in which case they're merely "incredibly profitable" making $199 off you instead of "ludicrously profitable" making $1999 off you had you used the API.

But to your point, re-reading the article, this is not what Simon is saying at all; he's just pointing out that he got to use ~$2000 "worth" of tokens on his $200 plan. Which makes total sense! Subscriptions are sticky, that's why the entire software industry moved towards subscription models (as much as we hate it); the person paying $200/month is more likely to stick around than the person who paid $2000 using the API.

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brazukadev 29 days ago
Which is a terrible metric sending a wrong message.
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aspenmartin 28 days ago
He’s just making a point that $100/mo subscription is cheaper than the API costs and that the same work would cost 10x as much on API pricing. It’s not some sort of swindle it’s a trade between consistent revenue that power users will overspend on but plenty of people will underspend (I’m on the underspend side) or pay-per-request service that makes more sense for say scaling out something custom (I run APIs a lot when I have say some pseudo labeling pipeline I want to scale to a lot of data. For this I typically use smaller models but lots of cases where you want larger models). What’s the wrong message here?
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