Setup DeepSeek-V3.2 Windows 10 with Native FP4

Setup DeepSeek-V3.2 Windows 10 with Native FP4

The fastest way to get this model running locally is via Docker.

Simply follow the directions outlined below.

Upon successful execution, you will fully enjoy everything you expected to achieve with this model.

🗂 Hash: 00096d91086f655266eff55d6e281031Last Updated: 2026-06-21



  • CPU: modern architecture (Zen 3 / Alder Lake minimum)
  • RAM: 48 GB needed to prevent memory swapping to disk
  • Disk Space: required: fast PCIe 4.0 drive for instant boots
  • GPU: high memory bandwidth GPU for next-gen local AI pipeline

The DeepSeek-V3.2 model sets a new benchmark in large language models with its massive 685 billion parameters and an extended 8K context window. It leverages an innovative mixture‑of‑experts architecture that dynamically routes queries to specialized sub‑networks, delivering both high accuracy and rapid inference. Compared to its predecessor, the model exhibits a 30% reduction in computational overhead while maintaining comparable performance on benchmark suites. The accompanying technical specifications are summarized in the table below, highlighting key metrics such as training data volume and inference latency. Its multimodal capabilities enable seamless integration with text, code, and image inputs, making it a versatile tool for developers and enterprises seeking state‑of‑the‑art AI solutions.

Parameters 685 B
Context Length 8K tokens
Training Data 2.5T tokens
Inference Latency <50 ms
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