How to Run GLM-4.5-Air-AWQ-4bit Windows

For the fastest local setup of this model, Docker is the best choice.

Follow the step-by-step instructions below.

The client handles the setup, pulling gigabytes of data automatically.

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

🔧 Digest: d30645351e262b50b8aefef4234bdcf1 • 🕒 Updated: 2026-06-22 Verify Processor: high single-core performance needed for token latency RAM: 48 GB needed to prevent memory swapping to disk Disk: high-speed SSD 120 GB to cache model layers 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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