How to Run Qwen3.5-9B-NVFP4

Deploying this model locally is quickest when done via Docker.

Use the instructions provided below to complete the setup.

The installer auto-downloads and deploys the entire model pack.

The automated installation script takes care of everything by tailoring the setup perfectly to your system specs.

📡 Hash Check: 25d6872c6f3585bfb6fb3936d4d1e2bd | 📅 Last Update: 2026-06-27



  • CPU: 8-core / 16-thread recommended for orchestration
  • RAM: enough space for background apps and OS overhead
  • Disk Space: 100 GB for multi-modal model vision components
  • GPU: modern architecture (Ada Lovelace / Ampere minimum)

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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