deepseek-v4-gguf PC with NPU with Native FP4

Homebrew offers the quickest path to setting up this model locally.

Simply follow the directions outlined below.

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

During setup, the script automatically determines and applies the best settings.

📦 Hash-sum → 8d37a6cd81ace6348460f8677cc8e99c | 📌 Updated on 2026-06-25



  • Processor: 6-core 3.5 GHz minimum required
  • RAM: required: 16 GB absolute minimum for small models
  • Disk Space: at least 100 GB for multiple local LLM variants
  • GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference

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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