Earlier quoted context omitted.
Do you have more info about this? I can't tell if you're being misled by the unfortunate "Mixture of Experts" terminology (which don't work the way you're describing), or alluding to something different. Or, maybe I'm wrong, but my understanding is: MoE is just an architecture to keep the activated weights smaller per token. The experts get routed basically token-by-token, and the "experts" themselves don't have a se…
No, this is an agent-level thing, not a feature of the model (ish, unsure for Fable). You talk to a smart, heavy model to build a plan composed of smaller steps. Then you have the heavy model spin up smaller, cheaper LLMs to actually implement the tasks. The heavy model is basically read-only in that mode. It can read files, execute tests, etc, but it can’t write code. It just tracks what needs to be done, offloads t…
Manually-specifying Sonnet or Opus is a multiplier on the base token rate; specifying Qwen fractions it. Left to its own, it presumably uses the heavier models to create the plan and orchestrate the work; the bite-sized task definitions are delegated to smaller models.