---
title: "Twice as Fast, Until It Isn't: Quantized Serving of Mid-Size Open LLMs"
source: "arXiv AI/CL/LG（论文）"
source_tier: "t2"
url: "https://arxiv.org/abs/2611.04380v1"
permalink: "https://feed.astralor.com/items/itm_bf3179c3c9e0bfe78296641d"
published: "2026-11-03T06:12:09.000Z"
score: 57
channel: "tech"
tags: ["LLM","推理效率","Twice","Fast","Until","Isn","Quantized Serving","Mid-Size Open LLMs"]
---

# Twice as Fast, Until It Isn't: Quantized Serving of Mid-Size Open LLMs

## 速览

A team serving a 9B-20B open-weight language model on vLLM or SGLang must choose a quantization recipe, and needs two numbers: the speedup over BF16 and the accuracy given up. We assemble every public measurement of the…

## 关键点

- A team serving a 9B-20B open-weight language model on vLLM or SGLang must choose a quantization recipe, and needs two numbers: the speedup over BF16 and the accuracy given up.
- We assemble every public measurement of these numbers that we could verify and find that the record supplies them only in pieces.
- Only two checkpoints, both INT4 builds of Gemma 3 12B, have both a vLLM timing and an accuracy score, and that score covers a single MMLU subject, one that the AWQ build was calibrated on.

## 全文

A team serving a 9B-20B open-weight language model on vLLM or SGLang must choose a quantization recipe, and needs two numbers: the speedup over BF16 and the accuracy given up. We assemble every public measurement of these numbers that we could verify and find that the record supplies them only in pieces. Only two checkpoints, both INT4 builds of Gemma 3 12B, have both a vLLM timing and an accuracy score, and that score covers a single MMLU subject, one that the AWQ build was calibrated on. The batch-1 timings predate current engine releases, AMD and Intel Gaudi have no timing in this band at all, and FP4 has none against BF16. The timings that do exist follow one rule. Decoding a small batch is limited by memory bandwidth, so 4-bit weights roughly double speed (2.12x for Qwen2.5-14B on an A100), but the gain vanishes once a large batch makes the GPU compute-bound (1.02x for Gemma 3 12B at batch size 256), where FP8 is the recipe that can still help. Many published accuracy deltas, including every HumanEval delta, lie within benchmark sampling noise. We close with a seven-item reporting checklist for future measurements.

---

引用前请核对原文;本文由星际流动整理:https://feed.astralor.com/items/itm_bf3179c3c9e0bfe78296641d