Deploy deepseek-v4-gguf on Copilot+ PC Quantized GGUF Local Guide Windows

Deploying this model locally is quickest when done via Docker.

Review and follow the instructions below.

No manual effort needed; the setup auto-ingests the large data.

Once launched, the setup wizard will detect your specs to configure the model for maximum efficiency.

📡 Hash Check: 1f9d76ab1ff2ffa3e3b25f7b7c29f1ce | 📅 Last Update: 2026-06-25



  • Processor: high single-core performance needed for token latency
  • RAM: enough space for background apps and OS overhead
  • Disk Space: 100 GB for multi-modal model vision components
  • Graphic Processor: RTX 3060 or RX 6600 for minimum 8B VRAM offloading

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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