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DeepSeek-R1-0528-NVFP4-v2 100% Private PC Local Guide

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

Review and follow the instructions below.

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

The deployment tool scans your environment and automatically chooses the ideal parameters for your OS.

📄 Hash Value: 51497095e70ae45fba490aaad4413610 | 📆 Update: 2026-06-24



  • Processor: 6-core 3.5 GHz minimum required
  • RAM: high-speed DDR5 memory preferred for CPU offloading
  • Storage:100 GB free space for HuggingFace cache folder
  • Graphics: 12 GB VRAM minimum required for basic quantization

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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