GLM-4.5-Air-AWQ-4bit Locally (No Cloud) with 1M Context

For the fastest local setup of this model, Docker is the best choice.

Use the instructions provided below to complete the setup.

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

The smart installation system will instantly find the perfect configuration for your specific hardware.

🗂 Hash: c22bff75d3af49e96aa4f5466d7b527b • Last Updated: 2026-06-25 Verify CPU: modern architecture (Zen 3 / Alder Lake minimum) RAM: minimum 16 GB for stable 8B model loading Disk Space:70 GB free space for full FP16 weights storage 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.

1. VRAM streaming balancer preventing texture degradation during long sessions
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