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DeepSeek-R1-0528-NVFP4-v2 PC with NPU 2026/2027 Tutorial

DeepSeek-R1-0528-NVFP4-v2 PC with NPU 2026/2027 Tutorial

For the fastest local setup of this model, Docker is the best choice.

Make sure to follow the instructions below.

The smart installation system will instantly find the perfect configuration for your specific hardware.

🛠 Hash code: b6fe6a5f496017619b46c4db9b74ff17 — Last modification: 2026-06-25
  • CPU: modern architecture (Zen 3 / Alder Lake minimum)
  • RAM: high-speed DDR5 memory preferred for CPU offloading
  • Disk: high-speed SSD 120 GB to cache model layers
  • Graphics: CUDA Compute Capability 8.0+ required for flash-attention

DeepSeek-R1-0528-NVFP4-v2 is a large language model optimized for low‑precision inference on NVIDIA’s Hopper architecture. It leverages NVFP4 data type to achieve higher throughput while maintaining state‑of‑the‑art accuracy. The model features a parameter count of 180 B and was trained on over 5 trillion tokens, enabling robust reasoning across diverse domains. Its inference latency averages 23 ms per token on a single A100‑80GB, making it suitable for real‑time applications. The design incorporates mixture‑of‑experts layers that dynamically route queries to specialized subnetworks, improving both efficiency and scalability. Below is a quick comparison of key technical specifications:

Parameter Count 180 B
Training Tokens 5 trillion
Inference Latency 23 ms/token
Precision NVFP4
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