---
title: "AWQ (Activation-aware Weight Quantization) - Air Market"
description: "You have a large language model and not enough GPU memory to run it comfortably. This compresses the model's weights down to four bits so it fits and runs faster, while paying attention to which weig…"
canonical: "https://airmarket.ai/app/awq-quantization"
---

[Air Market](/) / [Data & Analytics](/category/data) / AWQ (Activation-aware Weight Quantization)

Skill by [Orchestra Research](/@orchestra-research)

# AWQ (Activation-aware Weight Quantization)

Fit a large model onto the GPU memory you actually have

## What this does

You have a large language model and not enough GPU memory to run it comfortably. This compresses the model's weights down to four bits so it fits and runs faster, while paying attention to which weights matter so accuracy holds up. Reach for it when deployment is blocked by memory rather than by the model itself.

### Top 3 things it does for you

- Shrink a large model to fit limited GPU memory
- Speed up inference without losing much accuracy
- Compress an instruction-tuned or multimodal model

## Information

**AWQ (Activation-aware Weight Quantization) at a glance**

|  |  |
| --- | --- |
| Kind | Skill |
| Publisher | [Orchestra Research](/@orchestra-research) |
| Category | [Data & Analytics](/category/data) |
| Works with | Agent Skills - an open standard supported by 40+ agents |
| Version | 1.0.0 |
| Size | 24 KB |
| Licence | MIT |
| Repository | [orchestra-research/ai-research-skills](https://github.com/orchestra-research/ai-research-skills/tree/28f2d29236f2bade2eb92cadb2585189589a5828/10-optimization/awq) |
| GitHub stars | 11,987 (as of Nov 2026) |

## Security report

**Verified.** AIR scanned this exact version of AWQ (Activation-aware Weight Quantization) and flagged nothing. AIR's verdict: **safe**.

**What AWQ (Activation-aware Weight Quantization)'s check was run against**

|  |  |
| --- | --- |
| Commit | 28f2d29236f2bade2eb92cadb2585189589a5828 |
| Content hash | 34656635510531d30e2ff5e9e5d6beb3bf3c6948ec44f1c0f800402de7572eb4 |
| Files read | [Browse the files at this exact commit](https://github.com/orchestra-research/ai-research-skills/blob/28f2d29236f2bade2eb92cadb2585189589a5828/10-optimization/awq/SKILL.md) |

A scan is named by the exact content it read, not by a version number. A different version is a different artifact, and nothing here applies to a version AIR has not scanned.

[Read the full security report for AWQ (Activation-aware Weight Quantization)](/security/awq-quantization)

## About AWQ (Activation-aware Weight Quantization)

This is activation-aware weight quantization for four-bit LLM compression, offering a speedup with minimal accuracy loss.

Use it when deploying large models on limited GPU memory, when you want faster inference than GPTQ with better accuracy preservation, or when working with instruction-tuned and multimodal models.

The method won the MLSys 2024 Best Paper Award.

## What's inside

- SKILL.md - instructions
- references/advanced-usage.md - reference
- references/troubleshooting.md - reference

## Questions

### Is AWQ (Activation-aware Weight Quantization) safe to install?

AIR scanned this exact version of AWQ (Activation-aware Weight Quantization) and flagged nothing. AIR's verdict: safe. The verdict is named by the content that was read, at commit 28f2d29236f2, so it cannot drift onto a version nobody scanned. The full report is at https://airmarket.ai/security/awq-quantization.

### How do I install AWQ (Activation-aware Weight Quantization)?

Open https://airmarket.ai/app/awq-quantization on Air Market and use the install action: Air Market hands Claude a prompt naming this exact skill, and Claude sets it up. Source, pinned to the exact commit this listing describes: https://github.com/orchestra-research/ai-research-skills/tree/28f2d29236f2bade2eb92cadb2585189589a5828/10-optimization/awq. Install from that link, not the branch.

## Related on Air Market

- [More Data & Analytics listings](/category/data)
- [Everything by Orchestra Research](/@orchestra-research)

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Canonical URL: <https://airmarket.ai/app/awq-quantization>