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Quantizing an LLM to 4 bits with AWQ v1.0.0

Use this resource to compress an LLM to 4 bits for inference with little accuracy loss

New

  • 361 downloads
  • 134 likes
  • 212 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install awq-llm-quantization

With no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.

First time: connect the CLI with

npx --yes palatekit@latest login

The agent guides you through quantizing a model with AWQ or loading an already quantized one, then generating text. It explains when to prefer AWQ over GPTQ and how to configure quantization for your own model.

Mostly picked by

Updated November 2, 2026

Card for the “Quantizing an LLM to 4 bits with AWQ” skill

Details

Works in
Install guides
Generates with
Your agent's model
Licence
MIT

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What you get

  • SKILL.md: installation, loading and quantization
  • references/advanced-usage.md and troubleshooting.md: advanced settings and troubleshooting

Good fit for

  • You want to run a large model on limited hardware
  • You serve a chat model with vLLM and want to compress it

Not for

    Tags

    • quantization
    • 4-bit
    • llm
    • inference

    About

    You say

    “Quantize my Mistral 7B model to 4 bits with AWQ to serve it with vLLM.”

    Card for the “Quantizing an LLM to 4 bits with AWQ” skill

    Skill published by Orchestra Research under the MIT license, delivered in its original version.

    Show more

    How to use it

    1. Install the skill in your agent's skills folder
    2. Ask your agent to compress an LLM to 4 bits for inference with little accuracy loss
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE1.1 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • references/advanced-usage.md8.1 KB
    • references/troubleshooting.md7.9 KB
    • SKILL.md8.5 KB

    Origin and licence

    Listed unmodified

    Author
    Orchestra Research
    Source
    github.com/orchestra-research/ai-research-skills/tree/773a52944ba4747a18bd4ae9ade53fff041adcbc/10-optimization/awq
    Licence
    MIT

    Notice

    « awq-quantization » (Orchestra Research, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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