Homebrew offers the quickest path to setting up this model locally.
Use the instructions provided below to complete the setup.
An automated background process downloads all required large-scale files.
The installer will automatically analyze your hardware and select the optimal configuration.
DeepSeek-V4-Pro introduces a groundbreaking sparse‑attention architecture that dramatically cuts compute costs while retaining the ability to model long‑range contexts. With a staggering parameter count exceeding 1.5 trillion weights, the model delivers superior multilingual capabilities and nuanced reasoning. It has been trained on a meticulously curated training dataset of more than 5 trillion tokens, encompassing code repositories, scientific papers, and diverse conversational sources. Benchmark results highlight its state‑of‑the‑art performance across reasoning, coding, and factual QA tasks, often outpacing earlier models by double‑digit margins. Key technical specifications are summarized below:
| Metric | Value |
|---|---|
| Parameters | 1.5 T |
| Training Tokens | 5 T |
| Context Length | 8K |
| FLOPs per Token | 2.3×10^12 |
- Downloader pulling custom upscaler pipelines like SUPIR for local forge
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- Downloader pulling high-resolution Flux and Stable Diffusion XL checkpoints
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- Downloader pulling custom sentiment mapping checkpoints for offline data intelligence
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