The most rapid route to a local installation of this model is through Docker.
Follow the guidelines below to continue.
Then, simply start the container with the provided Docker command.
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 |
- VRAM optimization patch preventing low-res texture pop-in on 8GB cards
- Run DeepSeek-V4-Pro on Your PC Easy Build
- Matchmaking ping routing optimizer for localized community game networks
- Launch DeepSeek-V4-Pro Locally via Ollama 2
- Dedicated server configuration patch restoring removed legacy online play
- Deploy DeepSeek-V4-Pro Uncensored Edition Easy Build
- Uncensored asset restorer bringing back native audio variants and textures
- How to Launch DeepSeek-V4-Pro Locally via LM Studio One-Click Setup Full Method FREE