How to Deploy GLM-4.5-Air-AWQ-4bit PC with NPU Local Guide

The most rapid route to a local installation of this model is through Docker.

Make sure to follow the instructions below.

The deployment tool scans your environment and automatically chooses the ideal parameters for your OS.

🔧 Digest: 35494017388b3c68d0864bed0ff6dfb1 • 🕒 Updated: 2026-06-27 Verify Processor: high single-core performance needed for token latency RAM: required: 16 GB absolute minimum for small models Storage: extra room for future model updates and datasets Graphics: stable 30+ tk/s at 4-bit quantization on medium setup

The GLM-4.5-Air-AWQ-4bit is a compact yet powerful language model designed for both research and production environments. It leverages Activation‑aware Quantization (AWQ) to achieve high inference speed while preserving much of its original performance. With 6 billion parameters and an 8K token context window, the model can handle complex reasoning tasks and long‑form generation efficiently. The 4‑bit quantization reduces memory footprint and enables deployment on consumer‑grade hardware without noticeable loss in accuracy. Users appreciate its balanced trade‑off between size, speed, and capability, making it ideal for developers seeking a lightweight yet versatile AI assistant. Below is a quick overview of its key technical specifications.

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