Zero-Click Run DeepSeek-R1-0528-NVFP4-v2 Dummy Proof Guide

The fastest way to get this model running locally is via Docker.

Review and follow the instructions below.

1-click setup: the app automatically fetches the large weight files.

To guarantee smooth performance, the installation process auto-selects the best possible options for your PC.

📦 Hash-sum → 278ceb97d0eb3ccb1a50fb6a17cf52da | 📌 Updated on 2026-06-26



  • Processor: 6-core 3.5 GHz minimum required
  • RAM: 64 GB to avoid OOM crashes on large contexts
  • Disk Space: 80 GB NVMe SSD required for fast model weights loading
  • 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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