[amelius]

> Without training cost you can infer only the marginal cost of serving this kind of models.

Which is by far the most interesting number of the two.

> Moreover, you don't know the actual size of closed models (what if Fable is a 10T model? What if it's 1T?)

If you get close in output quality, then does that matter?

[embedding-shape]

> If you get close in output quality, then does that matter?

When you're trying to estimate/infer the costs of serving the tokens and even include the cost of training the weights in order to output tokens then yeah, why wouldn't that matter?

[jvuygbbkuurx]

That only matters if you are an investor not if you are a consumer.

[embedding-shape]

Well, or if you're participating in a discussion on HN where the sub-topic happens to be "if labs are subsidising tokens on API pricing" and literally the cost of serving the tokens is relevant to the sub-topic people are trying to discuss...

[solenoid0937]

Consumers want better models too, of course it matters

[vb-8448]

> Which is by far the most interesting number of the two.

Only if you don't have to continuously train new models, and you are not at a runway risk.