How to Deploy Qwen3.5-9B-AWQ No-Internet Version Local Guide

How to Deploy Qwen3.5-9B-AWQ No-Internet Version Local Guide

If you want the fastest local installation for this model, use Docker.

Use the instructions provided below to complete the setup.

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

To guarantee smooth performance, the installation process auto-selects the best possible options for your PC.

🧾 Hash-sum — ee71048348c3161f366b7a30f4dd891a • 🗓 Updated on: 2026-06-24



  • CPU: modern architecture (Zen 3 / Alder Lake minimum)
  • RAM: at least 32 GB in dual-channel mode for bandwidth
  • Storage:100 GB free space for HuggingFace cache folder
  • GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats

The Qwen3.5-9B-AWQ is a 9‑billion parameter language model designed for balanced performance and inference efficiency. It leverages Activation‑aware Quantization (AWQ) to reduce memory footprint while preserving high accuracy on a wide range of tasks. The model supports an extended context length of 8K tokens, enabling it to handle longer documents and complex reasoning chains. Trained on diverse multilingual data, it excels in code generation, dialogue, and factual QA across multiple languages. A compact yet powerful option for developers who need fast inference on consumer‑grade hardware. Key technical specifications are summarized below:

Spec Value
Parameters 9 B
Quantization AWQ (4‑bit)
Context Length 8K tokens
Primary Use‑cases Code, chat, QA
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