Launch GLM-4.5-Air-AWQ-4bit Windows 11 For Low VRAM (6GB/8GB) No-Code Guide

The fastest way to get this model running locally is via Docker.

Follow the step-by-step instructions below.

Once launched, the setup wizard will detect your specs to configure the model for maximum efficiency.

🛠 Hash code: 5ecf79f683944748435e3302d8ed3598 — Last modification: 2026-06-21
  • Processor: next-gen chip for heavy context processing
  • RAM: fast 5600MHz+ required to avoid memory bottlenecks
  • Disk: 150+ GB for high-context vector database storage
  • 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.

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