TokenGate: trainable module delivers up to 11x faster long-context prefill
CShorten30 · x · 2026-10-22
Matei Zaharia highlights Token-Gated Language Models: TokenGate is a trainable module that works with existing models to speed up long-context prefill by up to 11x by learning to skim context and conditionally forward only tokens that matter.
Author Liana Patel frames it as the next shift after dense-to-MoE: efficient LLMs will increasingly use conditional computation over a new scaling axis — context tokens.
Related event: TokenGate: Learned Token Pruning Speeds Up Long-Context Prefill Up to 11x(5 posts)→
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