Optimizers

Run DeepSeek-R1-0528-NVFP4-v2 Windows 10 No-Internet Version No-Code Guide

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Run DeepSeek-R1-0528-NVFP4-v2 Windows 10 No-Internet Version No-Code Guide

Homebrew offers the quickest path to setting up this model locally.

Follow the guidelines below to continue.

The loader auto-caches the model archive (several GBs included).

There is no manual tuning required; the builder deploys the best matching configuration.

🔍 Hash-sum: ff1804aedee95ea0a151c5d9a8f8dcbc | 🕓 Last update: 2026-06-24
  • CPU: multi-threading optimized for fast prompt processing
  • RAM: 48 GB needed to prevent memory swapping to disk
  • Disk Space: 100 GB for multi-modal model vision components
  • 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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