Comment by arrowleaf
14 hours ago
I would be surprised if AI prices reflect their current cost to provide the service, even inference costs. With so much money flowing into AI the goal isn't to make money, it's to grow faster than the competition.
14 hours ago
I would be surprised if AI prices reflect their current cost to provide the service, even inference costs. With so much money flowing into AI the goal isn't to make money, it's to grow faster than the competition.
From this article:
> For the purposes of this post, I’ll use the figures from the 100,000 “maximum”–Claude Sonnet and Opus 4.5 both have context windows of 200,000 tokens, and I run up against them regularly–to generate pessimistic estimates. So, ~390 Wh/MTok input, ~1950 Wh/MTok output.
Expensive commercial energy would be 30¢ per kWh in the US, so the energy cost implied by these figures would be about 12¢/MTok input and 60¢/MTok output. Anthropic's API cost for Opus 4.5 is $5/MTok input and $25/MTok output, nearly two orders of magnitude higher than these figures.
The direct energy cost of inference is still covered even if you assume that Claude Max/etc plans are offering a tenfold subsidy over the API cost.
Thank you for some good intel. Thats very interesting. But, I wonder how this affects supply pricing to other customers. Not that you haven't shown the direct power costs have been borne, but the more indirect ones remain for me.
I remain confident that most AI labs are not selling API access for less than it costs to serve the models.
If that's so common then what's your theory as to why Anthropic aren't price competitive with GPT-5.2?
I think it’s more instructive to look at providers like AWS than to compare with other AI labs. What’s the incentive for AWS to silently subsidise somebody else’s model when you run it on their infrastructure?
AWS are quite happy to give service away for free in vast quantities, but they do it by issuing credits, not by selling below cost.
I think it’s a fairly safe bet AWS aren’t losing money on every token they sell.
> I would be surprised if AI prices reflect their current cost to provide the service, even inference costs.
This has been covered a lot. You can find quotes from one of the companies saying that they'd be profitable if not for training costs. In other words, inference is a net positive.
You have to keep in mind that the average customer doesn't use much inference. Most customers on the $20/month plans never come close to using all of their token allowance.