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by theli0nheart 20 days ago
They may have good margins, but a few things are still true:

1. Much of those profits have to be immediately reinvested into model training runs to avoid being lapped by competitions.

2. Unit costs are irrelevant when the labs don't price per unit, and instead charge, for instance, $200 / month for $10k worth of tokens.

This isn't a steady state. Whatever the current situation is, I doubt it's sustainable.

1 comments

> 2. Unit costs are irrelevant when the labs don't price per unit, and instead charge, for instance, $200 / month for $10k worth of tokens.

Cost to generate all of the tokens divided by revenue generated by selling those tokens is what matters.

The subscription plans confuse a lot of people because that's what they see. They're not seeing the gigantic API bills from all of the tokens going into enterprise use cases.

The subscription plans are a small part of their income. Most users aren't maxing out 100% of their plan usage every week. I wouldn't be surprised if their average plan user was using less than 50% of their monthly quota each month.

Plans like that can produce a net increase in profit if they get consumers interested in the brand and pitching it at work. Giving them some extra token headroom on their $20/month or $100/month home plan is money well spent if it gets all of a company's developers advocating for enterprise plans with budgets exceeding $1000 per person.

enterprises are not dumb, they look at the cost of their ai investment and reevaluate it every quarter. Uber recently capped their AI spending per employee, and then there's this article a couple of days ago: https://finance.yahoo.com/technology/ai/articles/ceos-being-...
You’re all wrong and effing stupid

Until you bring reinvestment into your analysis stop posing