GLM-4.5-Air-AWQ-4bit Windows 11

For the fastest local setup of this model, enabling Windows Features is best.

Use the instructions provided below to complete the setup.

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

The automated script takes care of everything, tailoring the setup to your specs.

🔍 Hash-sum: ebdb1b04cd4b5dcfc4314fbd374c2361 | 🕓 Last update: 2026-06-25 Verify Processor: 6-core 3.5 GHz minimum required RAM: 48 GB needed to prevent memory swapping to disk Disk Space:70 GB free space for full FP16 weights storage Graphics: TensorRT-LLM / vLLM inference engine compatible chip

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.

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