Comment by bitmasher9
1 day ago
Usage is not going down. Take a look at their published revenue, it has a nice hockey stick shape.
I’m not making a bigger argument other than I disagree with that one datapoint you mentioned.
1 day ago
Usage is not going down. Take a look at their published revenue, it has a nice hockey stick shape.
I’m not making a bigger argument other than I disagree with that one datapoint you mentioned.
When you sell people 6 quarters for $1 they tend to buy a lot. Useage is a poor metric here given the capital intensive nature of this business. What matters is can they do this in a way that makes money to the degree that justifies the valuation, and there they have not yet demonstrated this is possible.
The internal metric that they are using is they get $2 for every $1 in inference. So, if you discount model development costs, they are selling the tokens for more than it costs them to generate a token. And this is before they start integrating their advertisment networks into the model. They see something as high as $8-11 per $1 of inference once purchasing and advertisments are incorporated.
The “but ads” logic fails basic sense checks. There isn’t enough ad money to go around to make up the gaps. With the big ad players like Google, Meta, and Amazon all shutting Anthropic out of their ecosystem there’s very little evidence that Anthropic can steal away enough of that as revenue to save itself.
In the “but they’ll slow down training and so will become more profitable” thinking is in big trouble given the pace of open models. They’ll then be even less competitive with free options and so even less reason to buy from Anthropic.
2 replies →
> So, if you discount model development costs, they are selling the tokens for more than it costs them to generate a token.
If you discount my expenses I am actually swimming in cash too.
It is absolutely moronic to discount the value of developing the thing from the profitability of the thing. Models to depreciate with time.
3 replies →
usage may shift to models run locally, albeit trained by the frontier labs, increasingly over time, though.
A floppy hockey stick.
Revenue growth q2 to q3 was significantly lower percentage wise than q1 to q2 and they swung back to net loss.
Yeah, the hockey stick is flipped in the wrong direction if you're looking at the past 4 months, plateauing after steady gains.