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

Please follow the instructions listed below to get started.

The system automatically triggers a cloud download for all heavy weights.

During setup, the script automatically determines and applies the best settings tailored to your machine.

🛠 Hash code: a1516fb2682ac330e40314610b6905fa — Last modification: 2026-06-25 Verify CPU: multi-threading optimized for fast prompt processing RAM: fast 5600MHz+ required to avoid memory bottlenecks Disk Space: 100 GB for multi-modal model vision components Graphics: CUDA Compute Capability 8.0+ required for flash-attention

DeepSeek-R1-0528-NVFP4-v2 is a large language model optimized for low‑precision inference on NVIDIA’s Hopper architecture. It leverages NVFP4 data type to achieve higher throughput while maintaining state‑of‑the‑art accuracy. The model features a parameter count of 180 B and was trained on over 5 trillion tokens, enabling robust reasoning across diverse domains. Its inference latency averages 23 ms per token on a single A100‑80GB, making it suitable for real‑time applications. The design incorporates mixture‑of‑experts layers that dynamically route queries to specialized subnetworks, improving both efficiency and scalability. Below is a quick comparison of key technical specifications:

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