---
id: 20260508-T0-11
title: "EdgeRazor实现大模型轻量化量化蒸馏"
title_en: "EdgeRazor Enables Lightweight LLMs via Quantization Distillation"
url: https://ai.daily.yangsir.net/daily/20260508-T0-11
issue_date: 2026-05-08
publish_date: 2026-05-07T04:00:00.000Z
category: research
source_name: "arXiv cs.LG (ML)"
source_url: https://arxiv.org/abs/2605.04062
---

# EdgeRazor实现大模型轻量化量化蒸馏

研究提出EdgeRazor轻量化框架，通过混合精度量化感知蒸馏技术压缩大模型。该技术将全精度模型转换为低比特表示，使其能在资源受限设备上运行。测试显示该方法在保持性能的同时显著减少模型大小。

## English Version

**EdgeRazor Enables Lightweight LLMs via Quantization Distillation**

Researchers introduced EdgeRazor, a lightweight framework that compresses LLMs via mixed-precision quantization-aware distillation. The technique converts full-precision models to low-bit representations for deployment on resource-constrained devices. Tests show it reduces model size while maintaining performance.

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**来源**：[arXiv cs.LG (ML)](https://arxiv.org/abs/2605.04062)

**详情页**：https://ai.daily.yangsir.net/daily/20260508-T0-11

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