GLM-4.5-Air-AWQ-4bit Locally via Ollama 2 Full Speed NPU Mode Full Method

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GLM-4.5-Air-AWQ-4bit Locally via Ollama 2 Full Speed NPU Mode Full Method

The most rapid route to a local installation of this model is through Docker.

Use the instructions provided below to complete the setup.

The client handles the setup, pulling gigabytes of data automatically.

The setup file includes an intelligent feature that instantly optimizes all configurations for your hardware profile.

🧩 Hash sum → 0b822c80236b6ed7148278232ec42b54 — Update date: 2026-06-26
  • Processor: 6-core 3.5 GHz minimum required
  • RAM: enough space for background apps and OS overhead
  • Disk Space: required: fast PCIe 4.0 drive for instant boots
  • GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats

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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