GLM-4.5-Air-AWQ-4bit PC with NPU One-Click Setup Offline Setup

For an instant local deployment, running a pre-configured shell script is ideal.

Make sure to follow the instructions below.

The loader auto-caches the model archive (several GBs included).

There is no manual tuning required; the builder deploys the best matching configuration.

📊 File Hash: 88da2a9d58e91f7163fb7639eaf5c877 — Last update: 2026-06-27 Verify Processor: Intel i5 or AMD Ryzen 5 for basic 7B models RAM: enough space for background apps and OS overhead Disk Space: at least 100 GB for multiple local LLM variants GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference

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.

1. Setup tool configuring local scratchpad memory for long contexts
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