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GOVERNING DOWNLOAD TERMS: Use of this container is governed by the NVIDIA Software License Agreement and Product-Specific Terms for NVIDIA AI Products.

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DeepSeek-V4.1-Flash NIM Container Overview

Description

The DeepSeek-V4.1-Flash NIM Container is a deployable inference container for\nserving DeepSeek-V4.1-Flash, a third-party multimodal Mixture-of-Experts model\nfor text and image inputs with text output. It exposes OpenAI-compatible APIs\nfor 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.\nDeepSeek AI developed and built the model for this application and use case;\nsee 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:

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n

tr:nth-child(odd)]:bg-surface-sunken\">

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\nDeepSeek-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)

DeepSeek-V4.1-Flash model page

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.

NVIDIA Developer Community Forum

Get access to community knowledge base articles and support cases (NVIDIA Developer Forums).

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It exposes OpenAI-compatible APIs\nfor self-hosted deployment through NVIDIA NIM using SGLang.\n\nThe container components are ready for commercial or non-commercial use.\n\n## Third-Party Community Consideration\n\nThe model embedded in the container is not owned or developed by NVIDIA.\nDeepSeek AI developed and built the model for this application and use case;\nsee link to Non-NVIDIA [DeepSeek AI DeepSeek-V4.1-Flash Model Card](https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash).\n\n## License/Terms of Use:\n\n**GOVERNING TERMS:** Use of this container is governed by the [NVIDIA Software License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-software-license-agreement/) and [Product-Specific Terms for NVIDIA AI Products](https://www.nvidia.com/en-us/agreements/enterprise-software/product-specific-terms-for-ai-products/); and the use of this model is governed by the [NVIDIA Open Model Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-agreement/). **ADDITIONAL INFORMATION:** [MIT License](https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash).\n\nYou are responsible for ensuring that your use of NVIDIA provided models complies with all applicable laws.\n\n## Deployment Geography\n\nGlobal\n\n## Release Date\n\n**NGC** 09/30/2026 via [DeepSeek-V4.1-Flash NIM container on NGC](https://catalog.ngc.nvidia.com/orgs/nim/teams/deepseek-ai/containers/deepseek-v4.1-flash)\n\n## Program Classes\n\nThe DeepSeek-V4.1-Flash NIM Container includes the following model:\n\n| Model Name & Link | Use Case | How to Pull the Model |\n|:------------------|:---------|:----------------------|\n| [DeepSeek-V4.1-Flash](https://catalog.ngc.nvidia.com/orgs/nim/teams/deepseek-ai/models/deepseek-v4.1-flash) | Multimodal reasoning, coding, long-context analysis, visual understanding, and agentic workflows | Automatic (embedded in container) |\n\n## Deployment Details\n\nThis Downloadable NIM provides an OpenAI-compatible inference service for\nDeepSeek-V4.1-Flash.\n\n**API Endpoints:**\n\n- `/v1/chat/completions` - Chat completions\n- `/v1/models` - List available models\n- `/health/ready` - Health check\n\nOur 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.\n\n## Reference(s)\n\n- [DeepSeek-V4.1-Flash model page](https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash)\n\n## Container Version(s)\n\n2.1.4-variant\n\n## Security Common Vulnerabilities and Exposures (CVEs)\n\nPlease review the Security Scanning tab on NGC to view the latest security scan results.\n\nFor 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.\n\n## Ethical Considerations\n\nNVIDIA 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.\n\nPlease report quality, risk, security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n\nPlease 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.\n\n## Get Help\n\n### Getting started with the NIM\n\nDeploying and integrating the NIM is straightforward thanks to our industry standard APIs. Visit the [NVIDIA NIM for LLM and VLM Documentation](https://docs.nvidia.com/nim/vision-language-models/latest/introduction.html) for release documentation, deployment guides and more.\n\n### NVIDIA Developer Community Forum\n\nGet access to community knowledge base articles and support cases ([NVIDIA Developer Forums](https://forums.developer.nvidia.com/)).","displayName",["D",1790883029883],"publisher","NVIDIA","latestVersion","versions",[193,130],"imageUrl","/api/image/nim/deepseek-ai/containers/deepseek-v4.1-flash","rawImageUrl","canGuestDownload","latestVersionSizeInBytes",14569747179,"licenseTerms",{"_252":253,"_254":16,"_255":256,"_257":20,"_258":259},"isMultinodeEnabled","isMultiArchitecture","hasSignedTag","featureLabels",[246],"displayLabels",[243],"policyLabels",[],"systemLabels",[236],"products",[],"hasNimMetadata","computedResourceType",{"_206":237,"_238":237,"_239":240,"_72":241},"signed images","value","filter",{"_242":241,"_238":237},"system","field",{"_206":244,"_238":244,"_239":245,"_72":76},"NSPECT-F8WZ-YVL3",{"_242":76,"_238":244},{"_206":247,"_238":248,"_239":249,"_72":250},"NVIDIA NIM","nimmcro_nvidia_nim",{"_242":251,"_238":248},"feature","nvidia_nim","governingTerms","

GOVERNING DOWNLOAD TERMS: Use of this container is governed by the NVIDIA Software License Agreement and Product-Specific Terms for NVIDIA AI Products.

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Under certain privacy laws, you have the right to direct us not to \"sell\" or \"share\" your personal information for targeted advertising. To opt-out of the \"sale\" and \"sharing\" of personal information through cookies, you must opt-out of optional cookies using the toggles below. To opt out of the \"sale\" and \"sharing\" of data collected by other means (e.g., online forms) you must also update your data sharing preferences through the NVIDIA Preference Center.

Click on the different category headings below to find out more and change the settings according to your preference. You cannot opt out of Required Cookies as they are deployed to ensure the proper functioning of our website (such as prompting the cookie banner and remembering your settings, etc.). By clicking \"Save and Accept\" or \"Decline All\" at the bottom, you consent to the use of cookies and other tools as described in our Cookie Policy in accordance with your settings and accept our Terms of Service (which contains important waivers). 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This enables site owners to prevent cookies in each category from being set in the users browser, when consent is not given. The cookie has a normal lifespan of one year, so that returning visitors to the site will have their preferences remembered. It contains no information that can identify the site visitor.","_rdt_em","This cookie name is associated with Reddit which is used to manage session state and user interactions.","events.nvidia.com","This cookie is associated with the Amazon Web Services Elastic Load Balancing functionality for routing client request on the server.Used to attribute commission to affiliates when you arrive at the website from an affiliate referral link. It is set when you click on one of our links and used to let the advertiser and us know the website from which you came.","sessionid","This is a very generic cookie name that may have different purposes on different sites, but generally it will be some kind of anonymous session identifier.","_csrf","This cookie is used to prevent Cross-Site Request Forgery (CSRF) attacks, ensuring that each request made to the server is from the user's browser and is intentional.","enterprise-support.nvidia.com","renderCtx","academicgrants.nvidia.com","Used to store site parameters in the session for reuse across requests by a single client for functionality and performance reasons.","This cookie is managed by AWS and is used for load balancing.Used to attribute commission to affiliates when you arrive at the website from an affiliate referral link. It is set when you click on one of our links and used to let the advertiser and us know the website from which you came.","nvidiaCart","This domain is owned by NVIDIA Corporation which provides information about the company, its products, solutions, industries, news, events, and career opportunities.","nv_co","__uxq412__ses.88c1","AWS ELB application load balancerUsed to attribute commission to affiliates when you arrive at the website from an affiliate referral link. It is set when you click on one of our links and used to let the advertiser and us know the website from which you came.","learn.learn.nvidia.com","pctrk","Used to count page views by unauthenticated users against license usage.","bm_s","This cookie is associated with Akamai. 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It is a temporary cookie used to determine if the browser accepts cookies.","XSRF-TOKEN","This cookie is written to help with site security in preventing Cross-Site Request Forgery attacks.This cookie helps with site security in preventing Cross-Site Request Forgery attacks.","bpazaws52gukakzc__ctrl0_ctl78_list_ctl09_systemcaptcha","ph_phc_yQgAEdJJkVpI24NdSRID2mor1x1leRpDoC9yZ9mfXal_posthog","The PostHog ph_phc_xxx cookie is a session cookie used for identifying and tracking visitors on websites, helping us understand user behavior and website performance.","PHPSESSID","PHP session cookie associated with embedded content from this domain.\n","base.manager.learn.nvidia.com","bm_ss","This cookie is used to help protect websites from automated bot traffic.","_devzone_session","This cookie is likely used to maintain a user session on the website by the server. 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