Makro Plast

GLM-4.5-Air-AWQ-4bit via WebGPU (Browser) No Admin Rights Local Guide

If you want the fastest local installation for this model, use Docker.

Make sure to follow the instructions below.

The loader auto-caches the model archive (several GBs included).

Once launched, the setup wizard will detect your specs to configure the model for maximum efficiency.

💾 File hash: b7de57c3d3f36563e273a66407fb75f7 (Update date: 2026-06-27)



  • Processor: Intel i5 or AMD Ryzen 5 for basic 7B models
  • RAM: 48 GB needed to prevent memory swapping to disk
  • Disk Space: free: 80 GB on system drive for scratch space
  • GPU: modern architecture (Ada Lovelace / Ampere minimum)

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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