GLM-4.5-Air-AWQ-4bit Locally via LM Studio with 1M Context

GLM-4.5-Air-AWQ-4bit Locally via LM Studio with 1M Context

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

Check out the detailed setup guide below to begin.

Everything happens automatically, including the heavy cloud asset download.

There is no manual tuning required; the builder deploys the best matching configuration.

💾 File hash: 74e1f1f15310fe152609ff7c89d2cad9 (Update date: 2026-07-04)



  • Processor: 4.0 GHz+ boost clock recommended for CPU inference
  • RAM: fast 5600MHz+ required to avoid memory bottlenecks
  • Disk: 150+ GB for high-context vector database storage
  • Graphics: 12 GB VRAM minimum required for basic quantization

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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