DeepSeek-R1-0528-NVFP4-v2 Windows 10 with Native FP4 Full Method

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

Use the instructions provided below to complete the setup.

The client handles the setup, pulling gigabytes of data automatically.

The script runs a quick hardware check to dynamically adjust parameters for elite speed.

📡 Hash Check: 1515981040c7a93b5c0efb390d950213 | 📅 Last Update: 2026-06-29



  • CPU: multi-threading optimized for fast prompt processing
  • RAM: 64 GB to avoid OOM crashes on large contexts
  • Disk Space: required: fast PCIe 4.0 drive for instant boots
  • Graphics: stable 30+ tk/s at 4-bit quantization on medium setup

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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