How to Run GLM-4.5-Air-AWQ-4bit Locally (No Cloud) Quantized GGUF Direct EXE Setup

How to Run GLM-4.5-Air-AWQ-4bit Locally (No Cloud) Quantized GGUF Direct EXE Setup

To install this model locally in the shortest time, opt for Docker.

Follow the sequence of steps detailed below.

The setup auto-streams the model assets (expect a multi-GB download).

The automated installation script takes care of everything by tailoring the setup perfectly to your system specs.

🧩 Hash sum → 91b46b9e5ec15a45877fd35f7e8cdbc3 — Update date: 2026-06-22



  • CPU: modern architecture (Zen 3 / Alder Lake minimum)
  • RAM: 32 GB highly recommended for 26B+ GGUF models
  • Disk Space:70 GB free space for full FP16 weights storage
  • Graphics: 12 GB VRAM minimum required for basic quantization

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.

Parameters 6 B
Context Length 8K tokens
Quantization AWQ 4‑bit
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