How to Deploy DeepSeek-R1-0528-NVFP4-v2

Running this model locally is fastest when deployed through a PowerShell script.

Check out the detailed setup guide below to begin.

The script takes care of fetching the multi-gigabyte model weights.

There is no manual tuning required; the builder deploys the best matching configuration.

📡 Hash Check: 34047554f48086b4e4694e8e567b4ffa | 📅 Last Update: 2026-07-04

Processor: high single-core performance needed for token latency
RAM: 32 GB or higher for smooth 32k context lengths
Storage:100 GB free space for HuggingFace cache folder
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:

Parameter Count	180 B
Training Tokens	5 trillion
Inference Latency	23 ms/token
Precision	NVFP4

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