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

For an instant local deployment, running a pre-configured shell script is ideal.

Just follow the guidelines provided below.

The engine will automatically fetch large dependencies in the background.

The program scans your VRAM and RAM to seamlessly apply optimal configurations.

🛡️ Checksum: e2c21388ca23ff1b4b4ba99d0cebc307 — ⏰ Updated on: 2026-07-04



  • CPU: AVX2/AVX-512 instruction set required for llama.cpp
  • RAM: 32 GB or higher for smooth 32k context lengths
  • Disk Space: free: 80 GB on system drive for scratch space
  • 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:

Parameters 9 B
Quantization NVFP4
Context Length 8K tokens
Training Data Web‑scale corpus

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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  • Qwen3.5-9B-NVFP4 on AMD/Nvidia GPU No Admin Rights Local Guide
  • Script downloading experimental weight array tensors for complex model recombination routines
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