To install this model locally in the shortest time, opt for a direct curl execution.

Refer to the action plan below to initialize the model.

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

You don’t need to tweak anything; the installer picks the highest performing setup.

🔐 Hash sum: fd9ab49796daa82a421d0257dbd88dfa | 📅 Last update: 2026-06-30 Verify Processor: 4.0 GHz+ boost clock recommended for CPU inference RAM: enough space for background apps and OS overhead Disk Space: 80 GB NVMe SSD required for fast model weights loading GPU: high memory bandwidth GPU for next-gen local AI pipeline

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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