GLM-4.5-Air-AWQ-4bit Uncensored Edition

Using the Windows Package Manager is the quickest way to trigger the setup.

Follow the guidelines below to continue.

The installer automatically pulls the model (could be multiple GBs).

There is no manual tuning required; the builder deploys the best matching configuration.

💾 File hash: 38a3023befb24fbb07e65efc589e792c (Update date: 2026-06-29)



  • CPU: AVX2/AVX-512 instruction set required for llama.cpp
  • RAM: fast 5600MHz+ required to avoid memory bottlenecks
  • Disk Space: 100 GB for multi-modal model vision components
  • GPU: high memory bandwidth GPU for next-gen local AI pipeline

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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