Run DeepSeek-R1-0528-NVFP4-v2 Using Pinokio No-Code Guide

If you want the fastest local installation for this model, use Docker.

Refer to the instructions below to proceed.

The installer auto-downloads and deploys the entire model pack.

Once launched, the setup wizard will detect your specs to configure the model for maximum efficiency.

🔧 Digest: 41faaf13f74373b8d101aa20b8312ffe • 🕒 Updated: 2026-06-22



  • CPU: 8-core / 16-thread recommended for orchestration
  • 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:

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