To install this model locally in the shortest time, opt for Docker.
Follow the step-by-step instructions below.
Then, simply start the container with the provided Docker command.
DeepSeek-V4-Pro introduces a groundbreaking sparseāattention architecture that dramatically cuts compute costs while retaining the ability to model longārange contexts. With a staggering parameter count exceeding 1.5āÆtrillion weights, the model delivers superior multilingual capabilities and nuanced reasoning. It has been trained on a meticulously curated training dataset of more than 5āÆtrillion tokens, encompassing code repositories, scientific papers, and diverse conversational sources. Benchmark results highlight its stateāofātheāart performance across reasoning, coding, and factual QA tasks, often outpacing earlier models by doubleādigit margins. Key technical specifications are summarized below:
| Metric | Value |
|---|---|
| Parameters | 1.5āÆT |
| Training Tokens | 5āÆT |
| Context Length | 8K |
| FLOPs per Token | 2.3Ć10^12 |
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