Setup Qwen3.5-397B-A17B-NVFP4 PC with NPU Zero Config

Setup Qwen3.5-397B-A17B-NVFP4 PC with NPU Zero Config

Using Docker is the absolute quickest way to install this model on your local machine.

Follow the guidelines below to continue.

1-click setup: the app automatically fetches the large weight files.

To guarantee smooth performance, the installation process auto-selects the best possible options for your PC.

🔧 Digest: b27ae307c92cd9f2f38864f7c3733f54 • 🕒 Updated: 2026-06-24



  • Processor: next-gen chip for heavy context processing
  • RAM: required: 16 GB absolute minimum for small models
  • Disk Space: free: 80 GB on system drive for scratch space
  • GPU: modern architecture (Ada Lovelace / Ampere minimum)

The Qwen3.5-397B-A17B-NVFP4 model represents a major leap in large language model efficiency, combining a 397‑billion parameter architecture with the ultra‑low‑precision NVFP4 data type.

By leveraging NVFP4 quantization, the model achieves a dramatic reduction in memory footprint while preserving near‑full‑precision performance, making it ideal for deployment on consumer‑grade GPUs.

Benchmarks show that the model delivers sub‑50 ms inference latency and a throughput of over 200 tokens per second on standard hardware, outperforming previous 400B‑scale models.

Its training pipeline incorporates a novel mixture‑of‑experts routing scheme that balances load across the A17B accelerator cluster, resulting in stable convergence and robust multilingual capabilities.

The integrated

Model Parameters Precision Latency (ms) Throughput (tokens/s)
Qwen3.5-397B-A17B-NVFP4 397B NVFP4 <50 >200

provides a quick comparison with competing models, highlighting parameter count, precision, latency, and throughput in a concise format.

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