Install Qwen3.5-9B-AWQ with Native FP4 Direct EXE Setup

To install this model locally in the shortest time, opt for a direct curl execution.

Follow the step-by-step instructions below.

All large files and heavy weights are downloaded automatically by the script.

Without any user input, the software calibrates parameters for optimal hardware usage.

🔍 Hash-sum: ffe166f5d34a9d94ca179a5fdb810efd | 🕓 Last update: 2026-06-23
  • Processor: Intel i5 or AMD Ryzen 5 for basic 7B models
  • RAM: required: 16 GB absolute minimum for small models
  • Disk Space: 80 GB NVMe SSD required for fast model weights loading
  • Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration

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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