How to Setup DeepSeek-R1-0528-NVFP4-v2 Quantized GGUF

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

Go through the configuration rules shown below.

The framework seamlessly downloads the massive neural network binaries.

The initial setup handles the heavy lifting, fine-tuning the environment for your device.

🖹 HASH-SUM: ec5bed57ff9568907309950ab665ffc5 | 📅 Updated on: 2026-06-27 Verify Processor: next-gen chip for heavy context processing RAM: 32 GB highly recommended for 26B+ GGUF models Disk Space: required: fast PCIe 4.0 drive for instant boots GPU: modern architecture (Ada Lovelace / Ampere minimum)

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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