The most efficient approach for a local installation is leveraging Docker containers.

Carefully read and apply the steps described below.

The setup auto-downloads all needed files (several GBs).

The installer diagnoses your environment to deploy the most compatible profile.

🔗 SHA sum: 36549f2302afb636ce6179a279ce9530 | Updated: 2026-07-08 Verify Processor: Intel i5 or AMD Ryzen 5 for basic 7B models RAM: at least 32 GB in dual-channel mode for bandwidth Disk Space: at least 100 GB for multiple local LLM variants Graphics: stable 30+ tk/s at 4-bit quantization on medium setup

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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• Script downloading IP-Adapter-FaceID weights for local consistent character creation layouts
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