DeepSeek-V4.1-Flash delivered as an NVIDIA NIM container: OpenAI-compatible APIs for text generation, reasoning, coding, agentic tool use and image understanding with a 1M-token context.
DeepSeek-V4.1-Flash NIM Container Overview
Description
The DeepSeek-V4.1-Flash NIM Container is a deployable inference container for serving DeepSeek-V4.1-Flash, a third-party multimodal Mixture-of-Experts model for text and image inputs with text output. It exposes OpenAI-compatible APIs for self-hosted deployment through NVIDIA NIM using SGLang.
The container components are ready for commercial or non-commercial use.
Third-Party Community Consideration
The model embedded in the container is not owned or developed by NVIDIA. DeepSeek AI developed and built the model for this application and use case; see link to Non-NVIDIA DeepSeek AI DeepSeek-V4.1-Flash Model Card.
License/Terms of Use:
GOVERNING TERMS: Use of this container is governed by the NVIDIA Software License Agreement and Product-Specific Terms for NVIDIA AI Products; and the 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 09/30/2026 via DeepSeek-V4.1-Flash NIM container on NGC
Program Classes
The DeepSeek-V4.1-Flash NIM Container includes the following model:
| Model Name & Link | Use Case | How to Pull the Model |
|---|---|---|
| DeepSeek-V4.1-Flash | Multimodal reasoning, coding, long-context analysis, visual understanding, and agentic workflows | Automatic (embedded in container) |
Deployment Details
This Downloadable NIM provides an OpenAI-compatible inference service for DeepSeek-V4.1-Flash.
API Endpoints:
/v1/chat/completions- Chat completions/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)
Container Version(s)
2.1.4-variant
Security Common Vulnerabilities and Exposures (CVEs)
Please review the Security Scanning tab on NGC to view the latest security scan results.
For certain open-source vulnerabilities listed in the scan results, NVIDIA provides a response in the form of a Vulnerability Exploitability eXchange (VEX) document. The VEX information can be reviewed and downloaded from the Security Scanning tab.
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. 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.
Please make sure you have proper rights and permissions for all input image and video content; if image or video includes people, personal health information, or intellectual property, the image or video generated will not blur or maintain proportions of image subjects included.
Get Help
Getting started with the NIM
Deploying and integrating the NIM is straightforward thanks to our industry standard APIs. Visit the NVIDIA NIM for LLM and VLM Documentation for release documentation, deployment guides and more.
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