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JustFit: 200K-Token LLM Serving on a 24 GiB Laptop with Just-in-Time State Management

Paper recorded by Signals 4 on 2026-09-15 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-15 on arXiv · recorded by Signals 4 on 2026-09-16

Category: cs.AI · 人工智能 · first seen 2026-09-16

Abstract

Capable open-weight models make local coding and reasoning attractive, but their context and execution state strain laptop memory. We present JustFit, an MLX-based inference runtime that combines KVExec for compressed KV execution, PhaseSwap for component residency, and StateTrans for state-preserving serving transitions. These mechanisms fuse reconstruction and coordinate just-in-time materializa

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#50 most recent of 300 cs.AI papers we have recorded · ↑ newer: Det-LIME: Detector-Aware, Multi-Instance Local Interpretable Model-Agn · ↓ older: Coupled Calibration and Learning: Mitigating Teacher Bias in LLM Disti
Cite this page: JustFit: 200K-Token LLM Serving on a 24 GiB Laptop with Just-in-Time State Management: the #50 most recent of 300 cs.AI papers we have recorded (as of 2026-09-15). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/justfit-200k-token-llm-serving-on-a-24-gib-laptop-with-just-in-time-state-manage.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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