Comment by mdp2021
14 hours ago
> Better... than 3.8 27B
How can a "6b active per token" MoE be better than a just released 27b in the same family? Possible maybe, but quite interesting and requiring some explanation.
Edit: ok, on second thought, probably because the small "experts" are really rich in specialized training compared to the dense model. Still raising questions about the details, e.g. the reasoning abilities (or all meta-skills) of a "6b per token" network compared to the dense capabilities...
Separating knowledge from reasoning so you only pay for what you use is a big rationale for MoE, the big problem being MoE training has historically been hard to get right. In a dense model every single token you're paying a cost to determine whether you're now talking about the flavor of durian.
Sure, the "6b subset" can be more knowledgeable on its area than a whole 27b generalist (and more efficient), but where is the simulated Intelligence encoded? A 6b subset as or more intelligent than a 27b raises the question of how metacognition skills are stored.
MOEs are built by training a second "router" model to identify which parts matter inside the dense model.
Think of MOE as ignoring noise, rather than a more efficient encoding of the data we teach it which ones can be ignored. Turning down the noise actually sharpens the results sometimes.
Modern LLM's are wildly inefficient.