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How to Autostart DeepSeek-R1-0528-NVFP4-v2 100% Private PC with 1M Context Direct EXE Setup

How to Autostart DeepSeek-R1-0528-NVFP4-v2 100% Private PC with 1M Context Direct EXE Setup

How to Autostart DeepSeek-R1-0528-NVFP4-v2 100% Private PC with 1M Context Direct EXE Setup

The fastest way to get this model running locally is via Docker.

Just follow the guidelines provided below.

The setup auto-streams the model assets (expect a multi-GB download).

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

🛠 Hash code: d9c4b344d870775cfc89e8f989be4fab — Last modification: 2026-06-22



  • Processor: 4.0 GHz+ boost clock recommended for CPU inference
  • RAM: at least 32 GB in dual-channel mode for bandwidth
  • Disk Space: at least 100 GB for multiple local LLM variants
  • Graphics: stable 30+ tk/s at 4-bit quantization on medium setup

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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