Setup DeepSeek-R1-0528-NVFP4-v2 with Native FP4

Setup DeepSeek-R1-0528-NVFP4-v2 with Native FP4

Deploying this model locally is quickest when done via a simple curl command.

Carefully read and apply the steps described below.

The system automatically triggers a cloud download for all heavy weights.

Your resources are automatically evaluated to lock in the premium configuration.

🖹 HASH-SUM: 430193a880394f135c0de52dc8412a0c | 📅 Updated on: 2026-07-03
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  • Processor: Intel i7 / Ryzen 7 for heavy Quantized models
  • RAM: 32 GB highly recommended for 26B+ GGUF models
  • Disk Space: free: 80 GB on system drive for scratch space
  • Graphics: TensorRT-LLM / vLLM inference engine compatible chip

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 Count180 B
Training Tokens5 trillion
Inference Latency23 ms/token
PrecisionNVFP4
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