Launch DeepSeek-R1-0528-NVFP4-v2 Fully Jailbroken 2026/2027 Tutorial

Running this model locally is fastest when deployed through Docker.

Follow the guidelines below to continue.

Once launched, the setup wizard will detect your specs to configure the model for maximum efficiency.

📘 Build Hash: 2a7a921ca85b06f349898f140c37ea47 • 🗓 2026-06-26 Verify Processor: high single-core performance needed for token latency RAM: required: 16 GB absolute minimum for small models Disk Space: at least 100 GB for multiple local LLM variants Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration

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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