DeepSeek-R1-0528-NVFP4-v2 Offline on PC Offline Setup

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

Go through the configuration rules shown below.

The loader auto-caches the model archive (several GBs included).

Without any user input, the software calibrates parameters for optimal hardware usage.

🔗 SHA sum: d58a24cb185fd670186c52c1f2925a80 | Updated: 2026-06-29 Verify Processor: 6-core 3.5 GHz minimum required RAM: enough space for background apps and OS overhead Disk Space:70 GB free space for full FP16 weights storage Graphics: CUDA Compute Capability 8.0+ required for flash-attention

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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