If you want the fastest local installation for this model, use standard pip packages.
Carefully read and apply the steps described below.
The engine will automatically fetch large dependencies in the background.
The program scans your VRAM and RAM to seamlessly apply optimal configurations.
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📤 Release Hash: 557d1a208b1ecc685d2d5a2ca6c0991f • 📅 Date: 2026-06-24
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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.
| Parameters | 6 B |
| Context Length | 8K tokens |
| Quantization | AWQ 4‑bit |
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