Using a native PowerShell script is the absolute quickest way to install this model.
Please follow the instructions listed below to get started.
The engine will automatically fetch large dependencies in the background.
Without any user input, the software calibrates parameters for optimal hardware usage.
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 |
- Script fetching custom model merges directly into KoboldAI directory structures
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- Setup tool mapping local CUDA environment variables for native nvcc code building
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- Setup utility enabling DirectML processing pathways for modern Arc graphics hardware layouts
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- Installer configuring secure multi-level authentication profiles for shared local node execution clusters
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