deepseek-v4-gguf Full Speed NPU Mode Easy Build Windows

The most rapid route to a local installation of this model is through Docker.

Follow the step-by-step instructions below.

Hands-free setup: the system self-downloads the heavy model files.

The deployment tool scans your environment and automatically chooses the ideal parameters for your OS.

📘 Build Hash: 496484abebdadd68341b627d9cf66b43 • 🗓 2026-06-24



  • Processor: next-gen chip for heavy context processing
  • RAM: 32 GB highly recommended for 26B+ GGUF models
  • Disk: 150+ GB for high-context vector database storage
  • GPU: high memory bandwidth GPU for next-gen local AI pipeline

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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