DeepSeek-R1-0528-NVFP4-v2 Locally via LM Studio For Low VRAM (6GB/8GB)

DeepSeek-R1-0528-NVFP4-v2 Locally via LM Studio For Low VRAM (6GB/8GB)

Setting up this model locally is incredibly fast if you use the native CMD prompt.

Follow the guidelines below to continue.

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

The program scans your VRAM and RAM to seamlessly apply optimal configurations.

🧩 Hash sum → 92a6a8c8ae94615fc954c30f4daf98ac — Update date: 2026-07-05



  • Processor: Intel i5 or AMD Ryzen 5 for basic 7B models
  • RAM: 32 GB highly recommended for 26B+ GGUF models
  • Storage:100 GB free space for HuggingFace cache folder
  • 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:

Parameter Count 180 B
Training Tokens 5 trillion
Inference Latency 23 ms/token
Precision NVFP4
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