Quick Run DeepSeek-R1-0528-NVFP4-v2 Quantized GGUF

Quick Run DeepSeek-R1-0528-NVFP4-v2 Quantized GGUF

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

Execute the commands and steps outlined below.

The tool automatically synchronizes and downloads the model database.

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

📘 Build Hash: c7e807477fd3e78482cf5e75f26378d6 • 🗓 2026-07-04



  • CPU: 8-core / 16-thread recommended for orchestration
  • RAM: minimum 16 GB for stable 8B model loading
  • Storage:100 GB free space for HuggingFace cache folder
  • 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:

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