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GLM-4.5-Air-AWQ-4bit Locally via Ollama 2 5-Minute Setup Windows

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

Use the instructions provided below to complete the setup.

The setup auto-downloads all needed files (several GBs).

The installer diagnoses your environment to deploy the most compatible profile.

🧮 Hash-code: e401303f9ebca04591eb669576cd3d7f • 📆 2026-06-27
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  • Processor: Intel i5 or AMD Ryzen 5 for basic 7B models
  • RAM: 32 GB or higher for smooth 32k context lengths
  • Disk Space: at least 100 GB for multiple local LLM variants
  • 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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