ljsysfurry/KV-Cache-Compression-Report

📄 KV Cache Compression for Text-Only LLMs

纯文本大语言模型 KV 缓存压缩 — 完整技术报告 | Full Technical Reports

Contents

File	Description
mla_absorbed_cache_report.md	🚀 MLA 吸收式缓存优化（中文）
mla_absorbed_cache_report_en.md	🚀 Absorbed MLA Cache Optimization (English)
kv_cache_compression_report.md	📊 KV 缓存压缩完整方案（中文）
kv_compress_plan.md	🗺 详细实施计划（中文）

🚀 Highlight: Absorbed MLA Cache (270KB → 8.4KB/token, 32×)

DeepSeek-V2-Lite MLA 优化，在 L40S 实测：

Approach	KV/token	Compression	Error
Standard MHA	270 KB	1x	—
Absorbed MLA	30.4 KB	8.9x	0
+ per-channel INT8	15.2 KB	17.8x	0.011
+ INT4 (extreme)	8.4 KB	32x	0.112

Single L40S: 1.24M tokens context.

Key Insight

Text-only models can be aggressively compressed (quantization + eviction), while reasoning models (R1-class) must be conservative (quantization + sliding window + tiered storage). Scenario classification matters more than the algorithm itself.

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Cloud LTE Studio · 2026-08-08 · GPL-3.0 License