Zero-Click Run DeepSeek-R1-0528-NVFP4-v2

A standalone PowerShell module provides the fastest route to local installation.

Refer to the instructions below to proceed.

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

Without any user input, the software calibrates parameters for optimal hardware usage.

🗂 Hash: 15b76c034914cb3a2b0132f4095b00db • Last Updated: 2026-07-02 Verify Processor: Intel i7 / Ryzen 7 for heavy Quantized models RAM: required: 16 GB absolute minimum for small models Disk: high-speed SSD 120 GB to cache model layers Graphics: TensorRT-LLM / vLLM inference engine compatible chip

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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