GLM-4.5-Air-AWQ-4bit Offline on PC

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

Make sure to follow the instructions below.

1-click setup: the app automatically fetches the large weight files.

The installer will automatically analyze your hardware and select the optimal configuration for your system.

🔒 Hash checksum: 456d9f74b35c53a7433714aa5ace5621 • 📆 Last updated: 2026-06-25 Verify Processor: high single-core performance needed for token latency RAM: enough space for background apps and OS overhead Disk Space: 100 GB for multi-modal model vision components GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats

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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