Quadrillion Param Costs: KV Cache, Context Length, Frontier Margins

The models of 2028-2031 get much bigger than the models of 2026, going from 10T total params in 2026 to maybe 240T params in 2028 [1] and then 1.4 quadrillion params in 2031, as I estimate in the previous post from HBM bandwidth/capacity, scale-up system size, pretraining compute, and scaling laws. Yet as I show in this post, if the 240T 2028 model is priced at $14/$70 per 1M input/output tokens (1.4x the API price of Mythos 5), it's going to have a 70% gross margin, and the same holds for the 1...