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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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SGLang Model-Free NIM

Description:

SGLang Model-Free NIM 2.1 is a NIM microservice container designed to support a broad range of LLMs. It includes a production-ready inference runtime with optimized inference engines from NVIDIA and the community—such as SGLang. When provided with an LLM at container runtime, stored in a Hugging Face format, the NIM identifies the model’s architecture and quantization, selects the appropriate inference backend, applies preconfigured settings for the model and backend, and begins serving the model for inference. For more information, see the NIM documentation and supported model architectures.

The container components are ready for commercial/non-commercial use.

License/Terms of Use:

GOVERNING TERMS: The NIM container is governed by the NVIDIA Software License Agreement and the Product-Specific Terms for NVIDIA AI Products.

The use of any models in this container is governed by the NVIDIA Open Model Agreement in addition to any terms which govern the specific models used.

You are responsible for ensuring that your use of any provided models complies with all applicable laws.

Deployment Geography:

Global

Deployment Details:

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.

Documentation

Visit the NIM Container LLM page for release documentation, deployment guides, and more.

Program Classes:

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

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

Inference Engine Name	Use Case	How to Pull the Inference Engine
SGLang Inference Engine	Execution for building custom large language models	Automatic

Security Common Vulnerabilities and Exposures (CVEs)

Please review the Security Scanning tab on NGC to view the latest security scan results.\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.

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 this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse.

Please report quality, risk, security vulnerabilities or NVIDIA AI Concerns here.

Get Help

Getting started with NVIDIA NIM

Deploying and integrating NVIDIA NIM is straightforward thanks to our industry standard APIs. Visit the NIM Container LLM page for release documentation, deployment guides and more.

NVIDIA Developer Community Forum

Get access to community knowledge base articles and support cases (https://forums.developer.nvidia.com/)

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When provided with an LLM at container runtime, stored in a Hugging Face format, the NIM identifies the model’s architecture and quantization, selects the appropriate inference backend, applies preconfigured settings for the model and backend, and begins serving the model for inference. For more information, see the NIM documentation and supported model architectures.\n\nThe container components are ready for commercial/non-commercial use.\n\n## **License/Terms of Use:**\n\n**GOVERNING TERMS:** The NIM container is governed by the [NVIDIA Software License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-software-license-agreement/) and the [Product-Specific Terms for NVIDIA AI Products](https://www.nvidia.com/en-us/agreements/enterprise-software/product-specific-terms-for-ai-products/).\n\nThe use of any models in this container is governed by the [NVIDIA Open Model Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-agreement/) in addition to any terms which govern the specific models used.\n\nYou are responsible for ensuring that your use of any provided models complies with all applicable laws.\n\n\n## **Deployment Geography:**\n\nGlobal \n\n## **Deployment Details:**\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**Documentation**\n\nVisit the [NIM Container LLM](https://docs.nvidia.com/nim/large-language-models/latest/introduction.html) page for release documentation, deployment guides, and more.\n\n## Program Classes:\n| Inference Engine Name | Use Case | How to Pull the Inference Engine|\n| :--- | :--- | :--- |\n| SGLang Inference Engine | Execution for building custom large language models | Automatic |\n\n## Security Common Vulnerabilities and Exposures (CVEs)\nPlease review the Security Scanning tab on NGC to view the latest security scan results.\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\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. When downloaded or used in accordance with our terms of service, developers should work with their internal developer team to ensure this model meets requirements for the relevant industry and use case and addresses 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\n# Get Help\n\n## Getting started with NVIDIA NIM\nDeploying and integrating NVIDIA NIM is straightforward thanks to our industry standard APIs. Visit the [NIM Container LLM](https://docs.nvidia.com/nim/large-language-models/latest/introduction.html) page for release documentation, deployment guides and more.\n\n### NVIDIA Developer Community Forum\nGet access to community knowledge base articles and support cases (https://forums.developer.nvidia.com/)","displayName","SGLang Model-Free NIM",["D",1792088695916],"publisher","NVIDIA","latestVersion","versions",[161,192],"imageUrl","/api/image/nim/nvidia/containers/sglang-model-free-nim-experimental","rawImageUrl","canGuestDownload","latestVersionSizeInBytes",13580977705,"licenseTerms",{"_261":262,"_263":16,"_264":265,"_266":20,"_267":268},"isMultinodeEnabled","isMultiArchitecture","hasSignedTag","featureLabels",[255],"displayLabels",[244,245,246],"policyLabels",[],"systemLabels",[237],"products",[],"hasNimMetadata","computedResourceType",{"_206":238,"_239":238,"_240":241,"_73":242},"signed images","value","filter",{"_243":242,"_239":238},"system","field",{"_206":253,"_239":253,"_240":254,"_73":77},{"_206":251,"_239":251,"_240":252,"_73":77},{"_206":247,"_239":248,"_240":249,"_73":77},"NVIDIA AI","soln_nvidia_ai",{"_243":250,"_239":248},"technology","NSPECT-8REV-8RUC",{"_243":77,"_239":251},"Experimental",{"_243":77,"_239":253},{"_206":256,"_239":257,"_240":258,"_73":259},"NVIDIA NIM","nimmcro_nvidia_nim",{"_243":260,"_239":257},"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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