How to Autostart Qwen3.5-9B-NVFP4 on AMD/Nvidia GPU with Native FP4 Windows

Running this model locally is fastest when deployed through a PowerShell script.

Simply follow the directions outlined below.

Hands-free setup: the system self-downloads the heavy model files.

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

???? Hash Check: 0c75c1b7a33863b4411b04cd6da6fa2f | ???? Last Update: 2026-06-24 Verify Processor: Intel i7 / Ryzen 7 for heavy Quantized models RAM: at least 32 GB in dual-channel mode for bandwidth Disk Space: 80 GB NVMe SSD required for fast model weights loading GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference

The Qwen3.5-9B-NVFP4 is a cutting‑edge language model designed for high performance and efficiency. Built on a 9‑billion parameter foundation, it leverages NVFP4 quantization to deliver faster inference while maintaining strong contextual understanding. Trained on a diverse web‑scale corpus, the model excels in reasoning, coding, and multilingual tasks, offering developers a versatile tool for production environments. Key specifications are shown below:

Its optimized memory footprint and support for FP4 hardware acceleration make it particularly suitable for edge deployments and cloud‑scale services.

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