Quick Run DeepSeek-R1-0528-NVFP4-v2 Locally via LM Studio No-Code Guide

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

Follow the step-by-step instructions below.

The installer automatically pulls the model (could be multiple GBs).

During setup, the script automatically determines and applies the best settings tailored to your machine.

🔗 SHA sum: 02863144fe16318151f6981bb083340b | Updated: 2026-06-24 Verify Processor: next-gen chip for heavy context processing RAM: enough space for background apps and OS overhead Disk: 150+ GB for high-context vector database storage GPU: modern architecture (Ada Lovelace / Ampere minimum)

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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