How to Setup Qwen3.5-4B-GGUF Windows 11 Full Speed NPU Mode Direct EXE Setup

The most efficient approach for a local installation is leveraging Docker containers.

Simply follow the directions outlined below.

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

The installer will automatically analyze your hardware and select the optimal configuration.

💾 File hash: e42ba5963d2a637d45f60f25ad37954b (Update date: 2026-06-24) Verify Processor: 6-core 3.5 GHz minimum required RAM: minimum 16 GB for stable 8B model loading Storage:100 GB free space for HuggingFace cache folder Graphics: stable 30+ tk/s at 4-bit quantization on medium setup

The **Qwen3.5-4B-GGUF** model delivers strong performance for a range of natural language tasks while maintaining a compact footprint. Built with 4B parameters and optimized for the GGUF quantization format, it balances speed and accuracy for both research and production environments. It supports a context window of up to 8192 tokens, enabling detailed reasoning and multi‑step problem solving without sacrificing latency. Benchmarks show the model achieves competitive perplexity scores on standard benchmarks while consuming less than 5 GB of GPU memory during inference. The integrated

below provides a quick comparison with similar open‑source models, highlighting its efficiency and ease of deployment.

Parameters	4 B
Context Length	8192 tokens
Quantization	GGUF
Memory Usage (inference)	<5 GB

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