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Comment by hermitcrab | Hacker News Reader

Companies generally charge whatever price they think will optimize their profit. This quite unrelated to what the service costs to run.

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There is also market separation in play: For the base service you only charge cost+small margin. For higher service levels you charge higher profit margins even though the additional service does not cost that much more to provide.

Best example: flight seats. Economy class fills the plane, but business and first class are the money makers [1].

[1] https://www.youtube.com/watch?v=BzB5xtGGsTc

Sure, and it wouldn't be surprising to see different pricing for realtime AI API usage vs slower (overnight, etc) response times (to fill up the seats and keep the hardware occupied). It remains to be seen how the dynamics of this works out though - function of cost of increasing capacity vs customer demand at various price points and service levels.

LLM pricing seems to still very much be up in the air though - models getting more efficient, serving hardware getting more efficient, use cases evolving, and not all providers operating with same business model (e.g. Meta, maybe China).

Yes, you see this all over the place. For example, Home and Professional versions of software products:

https://successfulsoftware.net/2013/02/28/how-i-increased-sa...

> This price is quite unrelated to what the service costs to run.

Well. It's noteworthy when the price is lower than the cost.

It's not that rare. But it is noteworthy, as it's not sustainable.

The optimal price is the optimal price, regardless of what the service costs to run.

But, yes, if the cost to run the service is X and the optimal price is <X, you have a problem.

The joke used to go "We lose money on every sale, but we make it up in volume”, but funnily enough, this financial logic adds up when you make it up with investor money.

No it’s not. Assume there is demand for 5000 units at $1 and 2000 units at $2. If it cost $0 to produce, then the profit is $5000/$4000 so you should price at $1. If it cost 90c to produce, then the profit is $500/$2200 so you should price at $2.

I was talking about software (the OP example), where there is a big fixed cost and (generally) a very low per unit cost. But I probably should have made that clearer. Things do indeed change when you have a significant per unit cost (e.g. manufactured goods).

Except that AI companies have different unit economics from SaaS businesses, requiring a rethinking of fundamentals, as laid out in this a16z post: https://a16z.com/the-new-business-of-ai-and-how-its-differen...

The per unit cost here is electricity. Those GPUs suck down enough during inference that it is not negligible.

AWS or Azure do charge per-usage, but not in line with usage of electricity. They're well above that.

Depends on the type of software. Some software have significant support costs.

>The optimal price is the optimal price, regardless of what the service costs to run.

such insight

Is it that noteworthy ? That has been the entire silicon valley playbook for the past.. decade ?

Grow at all cost with VC money, grab the market by offering unsustainably cheap prices, and when you have a monopoly, offer a slightly better or slightly worse version of the previous service (but hey, with an app that runs react!), at a slightly higher or same as before price (turns out profitability is important!), with much much worse working conditions for everyone involved (VC needs their money back, has to come from somewhere!)

Then look around confused when there is insane wealth inequality and social unrest.

money well spent if you arks me

Sure, and early adopters can usually expect to pay more.

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