DeepSeek-R1-0528-NVFP4-v2 on Copilot+ PC Zero Config 5-Minute Setup

If you need a near-instant local setup, just fetch files via a basic curl request.

Make sure you implement the steps mentioned below.

The engine will automatically fetch large dependencies in the background.

To save you time, the system will automatically determine efficient resource allocation.

🔍 Hash-sum: ac6dbc49aecca469079dedaed4bdcb18 | 🕓 Last update: 2026-06-23 Verify Processor: high single-core performance needed for token latency RAM: at least 32 GB in dual-channel mode for bandwidth 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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