---
title: "What LLM quantization works best for you? Q4_K_S or Q4_K_M"
url: https://daily.dev/posts/what-llm-quantization-works-best-for-you-q4-k-s-or-q4-k-m-jabfgq2xn
source_url: https://blog.gopenai.com/what-llm-quantization-works-best-for-you-q4-k-s-or-q4-k-m-910481632d93
type: article
source: "GoPenAI"
published: 2024-05-03T11:23:28.346Z
updated: 2026-03-15T05:52:00.405Z
tags: ["c++", "machine-learning", "performance"]
reading_time: 1
upvotes: 1
comments: 0
language: en
---

> ## Documentation Index
> Fetch the complete documentation index at: https://daily.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# What LLM quantization works best for you? Q4_K_S or Q4_K_M

**[GoPenAI](https://daily.dev/sources/gopenai)** · 1 min read · 1 upvotes · 0 comments

## Summary

Quantization methods for LLM, including Q3_K_S, Q4_K_M, Q4_0, and Q8_0, are discussed. The K_M models are recommended for their balance between size and perplexity. Implementation details of llama.cpp for quantization are provided.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://blog.gopenai.com/what-llm-quantization-works-best-for-you-q4-k-s-or-q4-k-m-910481632d93>

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---

Tags: [#c++](https://daily.dev/tags/c++), [#machine-learning](https://daily.dev/tags/machine-learning), [#performance](https://daily.dev/tags/performance)

[View this post on daily.dev](https://daily.dev/posts/what-llm-quantization-works-best-for-you-q4-k-s-or-q4-k-m-jabfgq2xn)