The fastest method for installing this model locally is by using Docker.

Execute the commands and steps outlined below.

1-click setup: the app automatically fetches the large weight files.

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

🔍 Hash-sum: bd19c26d2351fde81d81b351b4fe5773 | 🕓 Last update: 2026-06-30 Verify Processor: 4.0 GHz+ boost clock recommended for CPU inference RAM: 32 GB highly recommended for 26B+ GGUF models Storage: extra room for future model updates and datasets Graphics: stable 30+ tk/s at 4-bit quantization on medium setup

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:

• Setup utility configuring Amuse software for offline image generation via native ROCm layers
• Deploy DeepSeek-V4-Pro Windows 11 with Native FP4 Direct EXE Setup Windows FREE
• Installer deploying local face restoration scripts and pre-trained assets
• DeepSeek-V4-Pro Locally (No Cloud) FREE
• Script downloading IP-Adapter-FaceID weights for local consistent character creation render layouts
• DeepSeek-V4-Pro Using Pinokio Offline Setup FREE