The DeepSeek-V4-Pro Container is a deployable inference container for serving DeepSeek-V4-Pro, a third-party sparse Mixture-of-Experts language model for reasoning, coding, and agentic tasks.
DeepSeek-V4-Pro Overview
Description:
The DeepSeek-V4-Pro is a deployable inference container for serving DeepSeek-V4-Pro, a third-party sparse Mixture-of-Experts language model for reasoning, coding, and agentic tasks. The container provides OpenAI-compatible APIs for self-hosted deployment with a one-million-token context capability.
This container image is classified as a Pre-Release candidate (https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-software-license-agreement/)
Third-Party Community Consideration
The model embedded in the container is not owned or developed by NVIDIA. This model has been developed and built to a third-party's requirements for this application and use case; see link to Non-NVIDIA DeepSeek-V4-Pro Model Card.
License/Terms of Use:
GOVERNING TERMS: The NIM container is governed by the NVIDIA Software and Model Evaluation license; Use of this model is governed by the NVIDIA Open Model Agreement.
Additional Information: MIT License.
You are responsible for ensuring that your use of NVIDIA provided models complies with all applicable laws.
Deployment Geography:
Global
Release Date:
NGC 04/24/2026 via DeepSeek-V4-Pro NIM Container on NGC
Program Classes:
The DeepSeek-V4-Pro NIM Container includes the following model:
| Model Name & Link | Use Case | How to Pull the Model |
|---|---|---|
| DeepSeek-V4-Pro | Text generation, reasoning, coding, and agentic workflows | Automatic (embedded in container) |
Deployment Details
The DeepSeek-V4-Pro NIM Container exposes OpenAI-compatible APIs for seamless integration into existing applications and workflows.
API Endpoints:
/v1/chat/completions- Chat completions (streaming and non-streaming)/v1/models- List available models/health/ready- Health check
Our AI models are designed and/or optimized to run on NVIDIA GPU-accelerated systems. By leveraging NVIDIA's hardware (e.g. GPU cores) and software frameworks (e.g., CUDA libraries), the model achieves faster training and inference times compared to CPU-only solutions.
Reference(s):
Ethical Considerations:
NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal developer team to ensure these software components meet requirements for the relevant industry and use case and address unforeseen product misuse.
Please report quality, risk, security vulnerabilities or NVIDIA AI Concerns here.
Get Help
Getting started with the NIM
Deploying and integrating the NIM is straightforward thanks to our industry standard APIs. Visit the NIM Container page for release documentation, deployment guides and more.
NVIDIA Developer Community Forum
Get access to community knowledge base articles and support cases (NVIDIA Developer Forums).
Get Help
Getting started with the NIM
Deploying and integrating the NIM is straightforward thanks to our industry standard APIs. Visit the NVIDIA NIM documentation for release documentation, deployment guides and more.
NVIDIA Developer Community Forum
For support, visit the NVIDIA Developer Community Forum.