For the fastest local setup of this model, Docker is the best choice.
Review and follow the instructions below.
The client handles the setup, pulling gigabytes of data automatically.
The installer will automatically analyze your hardware and select the optimal configuration for your system.
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 |
- Script downloading custom layer weight arrays for experimental model merges
- Setup GLM-4.5-Air-AWQ-4bit with 1M Context No-Code Guide FREE
- Setup script for single-click local LLM environment deployment
- Install GLM-4.5-Air-AWQ-4bit Windows 10 No Python Required 5-Minute Setup Windows FREE
- Installer deploying local face restoration scripts and pre-trained assets
- Install GLM-4.5-Air-AWQ-4bit Windows 11 Dummy Proof Guide FREE
- Installer deploying complex ComfyUI workflows for Flux-ControlNet-Inpainting isolated hardware nodes
- How to Run GLM-4.5-Air-AWQ-4bit Offline on PC