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FreeToken: Efficient Edge-Native MoE Serving with Bandwidth-Adaptive Execution research paper by UC Berkeley, 2026

UC Berkeley · Aug 17, 2026 · Inference and efficiency · 2 citations · 86 upvotes · unverified

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What it shows

FreeToken is an edge-native Mixture-of-Experts serving system that dynamically maps computation and model state onto heterogeneous local hardware to run large open-weight models on personal machines.

UnverifiedHugging Face's summary; not yet checked by hand.

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About this paper
Authors
Shuo Yang, Xiaoze Fan, Melissa Pan and 8 more
arXiv
2608.16157 · PDF
Citations
2, 0 influential · Semantic Scholar
Upvotes
86 · Hugging Face
Code
github.com/FlashML-org/FreeToken
Lab
UC Berkeley

Changes

What changed
Influential citationsfirst count: 0Sep 25, 2026
Citationsfirst count: 2Sep 25, 2026
New paperFound by the weekly scan, unverifiedSep 25, 2026

Sources: each lab's own papers and arXiv, with citation and upvote counts from Semantic Scholar and Hugging Face. One-line summaries are for orientation, not a substitute for the paper. Logos via logo.dev; trademarks belong to their owners.

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