DeepSeek-R1-0528-NVFP4-v2 Locally via Ollama 2 Fully Jailbroken 5-Minute Setup

The most rapid route to a local installation of this model is through WSL2.

Review and follow the instructions below.

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

To save you time, the system will automatically determine efficient resource allocation.

🧾 Hash-sum — a82ebe4ecc24d2488ffd8f0b5150ce31 • 🗓 Updated on: 2026-07-05 Verify Processor: high single-core performance needed for token latency RAM: high-speed DDR5 memory preferred for CPU offloading Disk: 150+ GB for high-context vector database storage 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:

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