How to Launch GLM-4.5-Air-AWQ-4bit PC with NPU

For the fastest local setup of this model, enabling Windows Features is best.

Follow the sequence of steps detailed below.

Hands-free setup: the system self-downloads the heavy model files.

During setup, the script automatically determines and applies the best settings.

🧾 Hash-sum — 17c9aef68d132beb3c47a70a7ffa01e9 • 🗓 Updated on: 2026-06-29 Verify Processor: high single-core performance needed for token latency RAM: 64 GB to avoid OOM crashes on large contexts Disk: 150+ GB for high-context vector database 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.

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