If you need a near-instant local setup, just fetch files via a basic curl request.
Just follow the guidelines provided below.
The loader auto-caches the model archive (several GBs included).
The script runs a quick hardware check to dynamically adjust parameters for elite speed.
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 ۶ 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 | ۶ B |
| Context Length | 8K tokens |
| Quantization | AWQ 4‑bit |
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