How to Setup DeepSeek-V4-Pro Windows 11 with Native FP4 Easy Build

For an instant local deployment, running a pre-configured shell script is ideal.

Use the instructions provided below to complete the setup.

The setup auto-downloads all needed files (several GBs).

Your resources are automatically evaluated to lock in the premium configuration.

📊 File Hash: 17032fb711fbed21d9ec54d62216684d — Last update: 2026-06-27



  • CPU: modern architecture (Zen 3 / Alder Lake minimum)
  • RAM: 32 GB highly recommended for 26B+ GGUF models
  • Storage:100 GB free space for HuggingFace cache folder
  • Graphics: CUDA Compute Capability 8.0+ required for flash-attention

DeepSeek-V4-Pro introduces a groundbreaking sparse‑attention architecture that dramatically cuts compute costs while retaining the ability to model long‑range contexts. With a staggering parameter count exceeding 1.5 trillion weights, the model delivers superior multilingual capabilities and nuanced reasoning. It has been trained on a meticulously curated training dataset of more than 5 trillion tokens, encompassing code repositories, scientific papers, and diverse conversational sources. Benchmark results highlight its state‑of‑the‑art performance across reasoning, coding, and factual QA tasks, often outpacing earlier models by double‑digit margins. Key technical specifications are summarized below:

Metric Value
Parameters 1.5 T
Training Tokens 5 T
Context Length 8K
FLOPs per Token 2.3×10^12
  • Installer deploying local chat clients with DeepSeek-V3 API-mirror setups
  • How to Setup DeepSeek-V4-Pro on AMD/Nvidia GPU Full Speed NPU Mode 2026/2027 Tutorial FREE
  • Setup tool updating local miniconda environments for running PyTorch 2.6+ scripts directly
  • How to Deploy DeepSeek-V4-Pro Locally via LM Studio Quantized GGUF Dummy Proof Guide
  • Setup utility linking custom local LLM pipelines with federated LibreChat instances
  • Full Deployment DeepSeek-V4-Pro Locally (No Cloud) For Beginners