Deploying this model locally is quickest when done via Docker.
Follow the step-by-step instructions below.
The setup auto-streams the model assets (expect a multi-GB download).
The deployment tool scans your environment and automatically chooses the ideal parameters for your OS.
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:
| Parameter Count | 180 B |
| Training Tokens | 5 trillion |
| Inference Latency | 23 ms/token |
| Precision | NVFP4 |
- Centralized mod manager featuring automated dependency sorting algorithms
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- VR performance wrapper for running heavy flat-screen mods on VR headsets
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- Intro logo and splash screen bypass for instant title menu loading
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