Overview
awq-quantization is an open-source workflow skill for Claude Code and compatible agents, published by Orchestra-Research. Its author describes it as: “Activation-aware weight quantization for 4-bit LLM compression with 3x speedup and minimal accuracy loss. Use when deploying large models (7B-70B) on limited GPU memory, when you need faster inference than GPTQ with b…”. The project has 12k stars on GitHub and is available under the MIT license. Add it to your setup with `/plugin marketplace add Orchestra-Research/AI-Research-SKILLs`.
What awq-quantization does
4-bit quantization that preserves salient weights based on activation patterns, achieving 3x speedup with minimal accuracy loss.
Best for
What’s inside
The SKILL.md for awq-quantization is organised into these sections:
- When to use AWQ
- Quick start
- Installation
- Load pre-quantized model
- Quantize your own model
- AWQ vs GPTQ vs bitsandbytes
- Kernel backends
- GEMM (default, batch inference)
- GEMV (single-token generation)
- Marlin (Ampere+ GPUs)
- ExLlamaV2 (AMD compatible)
- HuggingFace Transformers integration
Installation
Add awq-quantization to your agent with:
/plugin marketplace add Orchestra-Research/AI-Research-SKILLsReview a skill’s source before installing it — skills can instruct your agent to run commands. This command comes from the skill’s public repository, which is the source of truth for setup steps. New to skills? Read how to install Claude Code skills.
Supported agents
- Claude Code — ships a claude code plugin marketplace
- Codex — declared in the repository topics
License
awq-quantization is published under the MIT license.
Strengths
- Clear MIT license — safe to read and adapt within its terms
- Ships in Orchestra-Research/AI-Research-SKILLs, an established project with 11,807 GitHub stars
- Works with Claude Code, Codex
Author
Topics
Frequently asked questions
- What does awq-quantization do?
- Activation-aware weight quantization for 4-bit LLM compression with 3x speedup and minimal accuracy loss. Use when deploying large models (7B-70B) on limited GPU memory, when you need faster inference than GPTQ with better accuracy preservation, or for instruction-tuned and multimodal models. MLSys 2024 Best Paper Award winner.
- How do I install awq-quantization?
- Run /plugin marketplace add Orchestra-Research/AI-Research-SKILLs in your agent, then reload your skills. Review the source at https://github.com/Orchestra-Research/AI-Research-SKILLs before installing.
- Is awq-quantization free to use?
- Yes. awq-quantization is free and open source under the MIT license, so you can read, run, and adapt it within that license's terms.
- Which agents does awq-quantization work with?
- awq-quantization lists Claude Code and Codex — named in its SKILL.md, its plugin marketplace or its repository topics. Skills use the portable SKILL.md format, so other agents that read that format may load it too.
- Where does awq-quantization come from?
- awq-quantization ships inside Orchestra-Research/AI-Research-SKILLs, a repository that contains 41 catalogued skills in total. The repository's 11,807 GitHub stars apply to that whole collection, not to this skill on its own.