How to Deploy DeepSeek-V4-Pro Using Pinokio with Native FP4 For Beginners

How to Deploy DeepSeek-V4-Pro Using Pinokio with Native FP4 For Beginners

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

Execute the commands and steps outlined below.

An automated background process downloads all required large-scale files.

The script runs a quick hardware check to dynamically adjust parameters for elite speed.

📎 HASH: 09b21c47fe35e044514a2a4726bccdad | Updated: 2026-07-06



  • Processor: high single-core performance needed for token latency
  • RAM: high-speed DDR5 memory preferred for CPU offloading
  • Disk Space:70 GB free space for full FP16 weights storage
  • Graphics: TensorRT-LLM / vLLM inference engine compatible chip

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
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