Install GLM-4.5-Air-AWQ-4bit Zero Config

Deploying locally takes the least amount of time when executed through native OS tools.

Please adhere to the deployment steps listed below.

The engine will automatically fetch large dependencies in the background.

The setup file includes a feature that instantly optimizes all configurations.

🛡️ Checksum: d1d7f3739f8556260cc2671f0e8dfe79 — ⏰ Updated on: 2026-06-26

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Processor: high single-core performance needed for token latency
RAM: required: 16 GB absolute minimum for small models
Disk Space:70 GB free space for full FP16 weights storage
Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration

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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