Quick Run GLM-4.5-Air-AWQ-4bit Windows 10 Uncensored Edition

Running this model locally is fastest when deployed through a PowerShell script.

Make sure to follow the instructions below.

The framework seamlessly downloads the massive neural network binaries.

The configuration wizard runs silently to set up the model for peak performance.

💾 File hash: b64040bcee69e03967d8ca2c3fa013e0 (Update date: 2026-07-04)

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CPU: modern architecture (Zen 3 / Alder Lake minimum)
RAM: required: 16 GB absolute minimum for small models
Disk Space: free: 80 GB on system drive for scratch space
Graphics: stable 30+ tk/s at 4-bit quantization on medium setup

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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