Qwen3.5-397B-A17B-NVFP4 with Native FP4 Direct EXE Setup

Qwen3.5-397B-A17B-NVFP4 with Native FP4 Direct EXE Setup

The shortest path to running this model is by activating Hyper-V features.

Use the instructions provided below to complete the setup.

The installer automatically pulls the model (could be multiple GBs).

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

📡 Hash Check: ecf42dbfb6dffb0ab7d81a7ca5ca9be3 | 📅 Last Update: 2026-06-30



  • Processor: Intel i7 / Ryzen 7 for heavy Quantized models
  • RAM: 64 GB to avoid OOM crashes on large contexts
  • Disk Space: at least 100 GB for multiple local LLM variants
  • Graphic Processor: RTX 3060 or RX 6600 for minimum 8B VRAM offloading

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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