so after your edit it would be (just to clarify):

    I use ____ ___ = downscale_common(lightweight1(.)) + downscale_common(lightweight2(.)) ?

You generate blocks of 2 at a time yes. In general, k. As you can imagine, larger k performs worse. LLM(I like cats) is very likely to continue with "because they", but beyond that, there's too many possibilities. LLM(I like cats because they are) = small and cute and they meow, while LLM(I like cats because they eat) = all the rats in my garden.

If you try to predict the whole thing at once you might end up with

I like cats because they are all the rats and they garden

> Overlap

Check out an inference method called self-speculative decoding which solves(somewhat) the above problem of k-token prediction, which does overlap the same ___ across multiple computations.