AWQ
The fastest way to get this model running locally is via Optional Features.
Follow the straightforward walkthrough provided below.
The loader auto-caches the model archive (several GBs included).
The initial setup handles the heavy lifting, fine-tuning the environment for your device.
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 |
- Script automating download of vision encoders for multi-modal parsing
- Qwen3.5-9B-AWQ Quantized GGUF
- Script downloading specialized multi-column layout parsing models for PDF engines
- Deploy Qwen3.5-9B-AWQ Windows 11 No-Code Guide
- Setup tool configuring MemGPT memory layers alongside persistent local GGUF execution nodes
- Install Qwen3.5-9B-AWQ 100% Private PC with 1M Context No-Code Guide
- Downloader pulling specialized textual inversion files for photographic facial fixes
- Full Deployment Qwen3.5-9B-AWQ with Native FP4 No-Code Guide FREE
- Downloader pulling specialized offline translation models for LibreTranslate network cluster server nodes
- Launch Qwen3.5-9B-AWQ FREE