Deploy DeepSeek-R1-0528-NVFP4-v2 No-Internet Version No-Code Guide

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

Review and follow the instructions below.

The download manager will automatically pull several gigabytes of data.

The configuration wizard runs silently to set up the model for peak performance.

📡 Hash Check: de5cfbdf72ad203072eecb79356e8a33 | 📅 Last Update: 2026-06-23 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: 48 GB needed to prevent memory swapping to disk Disk Space: 80 GB NVMe SSD required for fast model weights loading GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference

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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