How to Deploy DeepSeek-R1-0528-NVFP4-v2 Using Pinokio with 1M Context

If you need a near-instant local setup, just fetch files via a basic curl request.

Just follow the guidelines provided below.

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

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

🖹 HASH-SUM: 7986c77829878c12bcfd8a3c6428533c | 📅 Updated on: 2026-07-01 Verify Processor: Intel i7 / Ryzen 7 for heavy Quantized models RAM: 48 GB needed to prevent memory swapping to disk Disk Space: 100 GB for multi-modal model vision components 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:

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