Looped Transformers cut parameters but inflate KV cache; flashloop exploits cross-loop redundancy
WanqiYang1 · x · 2026-09-26
Looped Transformers enable deeper computation without more parameters, but every loop adds both compute and KV cache overhead. The author argues that the key to inference efficiency is exploiting cross-loop redundancy, and ships a practical starting point: an open-source package called flashloop, installable via pip install flashloop, to optimize looped-model inference.
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