---
title: "Benchmarking KV-Cache Optimizations across Task Quality and System Performance for Long-Context Serving — Stuff That Spins"
description: "arXiv:2607.05399v1 Announce Type: new Abstract: Large language model serving is increasingly limited by KV-cache growth under long-context workloads, yet exist…"
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date: "2026-07-08T04:00:00+00:00"
modified: "2026-07-08T06:03:31.596236+00:00"
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# Benchmarking KV-Cache Optimizations across Task Quality and System Performance for Long-Context Serving

**Source:** Unknown  
**Published:** July 8, 2026  
**Original:** https://arxiv.org/abs/2607.05399  

## On this page

- [Overview](#overview)

<a id="overview"></a>

## Overview

arXiv:2607.05399v1 Announce Type: new Abstract: Large language model serving is increasingly limited by KV-cache growth under long-context workloads, yet existing KV-cache compression techniques are difficult to compare because they were evaluated on different models, tasks, budgets, and serving stacks. This paper presents a workload-aware benchmark of representative KV-cache optimization mechanisms spanning quantization, pruning, and merging, including KIVI, TurboQuant, SnapKV, and CaM, evaluat

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