Deploy Qwen3.5-397B-A17B-NVFP4 Windows

Deploy Qwen3.5-397B-A17B-NVFP4 Windows

🛡️ Checksum: 26355c92b7d5d8c969dc805713920605 — ⏰ Updated on: 2026-07-18



  • Processor: next-gen chip for heavy context processing
  • RAM: 32 GB or higher for smooth 32k context lengths
  • Disk Space:70 GB free space for full FP16 weights storage
  • GPU: modern architecture (Ada Lovelace / Ampere minimum)

The Qwen3.5-397B-A17B-NVFP4: A Breakthrough in Large Language Model Efficiency

This latest model marks an unprecedented achievement in large language model efficiency, integrating a 397-billion parameter architecture with the ultra-low-precision NVFP4 data type. By leveraging NVFP4 quantization, the model achieves a substantial reduction in memory footprint while preserving near-full-precision performance, making it ideal for deployment on consumer-grade GPUs.

Key Performance Metrics

  • Sub-50ms inference latency
  • Throughput of over 200 tokens per second
  • Better than previous 400B-scale models in terms of performance and efficiency

Mixture-of-Experts Routing Scheme

The Qwen3.5-397B-A17B-NVFP4’s 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.

Model Parameters Precision Latency (ms) Throughput (tokens/s)
Qwen3.5-397B-A17B-NVFP4 397B NVFP4 50 200
Degenerate Model 100B FP16 150 100

Potential Applications and Deployment Scenarios

• Consumer-grade GPUs for efficient inference• Multilingual applications with robust capabilities• High-performance computing for AI research

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