Qwen3.6-27B NIM Container Overview

Description

The Qwen3.6-27B NIM Container is a deployable inference container for serving Qwen3.6-27B, a third-party multimodal dense model capable of processing text, image, and video inputs for text generation. The container provides an OpenAI-compatible API for self-hosted deployment, powered by the SGLang backend across supported NVIDIA GPU platforms.

The container components are ready for commercial use.

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 Qwen3.6-27B Model Card.

License/Terms of Use:

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

Additional Information: Apache 2.0 License.

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

Deployment Geography:

Global

Release Date:

NGC 04/23/2026 via Qwen3.6-27B NIM Container on NGC

Program Classes:

The Qwen3.6-27B 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
Qwen3.6-27B	Multimodal text generation, agentic coding, visual understanding, reasoning	Automatic (embedded in container)

Deployment Details

The Qwen3.6-27B NIM Container exposes an OpenAI-compatible chat completions API 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

Operating System: Linux

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):

Qwen3.6-27B NVIDIA Model Card
Qwen3.6-27B on HuggingFace

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 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.

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 NVIDIA NIM documentation for release documentation, deployment guides and more.

NVIDIA Developer Community Forum

For support, visit the NVIDIA Developer Community Forum.

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The container provides an OpenAI-compatible API for self-hosted deployment, powered by the SGLang backend across supported NVIDIA GPU platforms.\n\n*The container components are ready for commercial use.*\n\n## Third-Party Community Consideration\nThe 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 [Qwen3.6-27B Model Card](https://huggingface.co/Qwen/Qwen3.6-27B).\n\n## License/Terms of Use:\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 [Product-Specific Terms for NVIDIA AI Products](https://www.nvidia.com/en-us/agreements/enterprise-software/product-specific-terms-for-ai-products/). Use of this model is governed by the [NVIDIA Open Model License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/).\n\nAdditional Information: [Apache 2.0 License](https://huggingface.co/Qwen/Qwen3.6-27B).\n\nYou are responsible for ensuring that your use of NVIDIA provided models complies with all applicable laws.\n\n### Deployment Geography:\nGlobal\n\n## Release Date:\n**NGC** 04/23/2026 via [Qwen3.6-27B NIM Container on NGC](https://catalog.ngc.nvidia.com/orgs/nim/teams/qwen/containers/qwen3.6-27b)\n\n## Program Classes:\n\nThe Qwen3.6-27B NIM Container includes the following model:\n\n| Model Name & Link | Use Case | How to Pull the Model |\n|:------------------|:---------|:---------------------|\n| [Qwen3.6-27B](https://catalog.ngc.nvidia.com/orgs/nim/teams/qwen/models/qwen3.6-27b) | Multimodal text generation, agentic coding, visual understanding, reasoning | Automatic (embedded in container) |\n\n## Deployment Details\n\nThe Qwen3.6-27B NIM Container exposes an OpenAI-compatible chat completions API for seamless integration into existing applications and workflows.\n\n**API Endpoints:**\n* `/v1/chat/completions` — Chat completions (streaming and non-streaming)\n* `/v1/models` — List available models\n* `/health/ready` — Health check\n\n**Operating System:** Linux\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* [Qwen3.6-27B NVIDIA Model Card](https://catalog.ngc.nvidia.com/orgs/nim/teams/qwen/models/qwen36-27b)\n* [Qwen3.6-27B on HuggingFace](https://huggingface.co/Qwen/Qwen3.6-27B)\n\n\n## Ethical Considerations:\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 these software components meet requirements for the relevant industry and use case and address unforeseen product misuse.\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\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 the NIM\n\nDeploying and integrating the NIM is straightforward thanks to our industry standard APIs. Visit the [NVIDIA NIM documentation](https://docs.nvidia.com/nim/large-language-models/latest/about-nim-llm/overview.html) for release documentation, deployment guides and more.\n\n### NVIDIA Developer Community Forum\n\nFor support, visit the [NVIDIA Developer Community Forum](https://forums.developer.nvidia.com/).",["D",1776987918507],"Qwen",[257,314],"/api/image/nim/qwen/containers/qwen3.6-27b",12746394465,"hasSignedTag",[308],[306],[],[302],[],{"_95":303,"_150":303,"_151":304,"_153":305},"signed images",{"_155":305,"_150":303},"system",{"_95":149,"_150":149,"_151":307,"_153":154},{"_155":154,"_150":149},{"_95":309,"_150":310,"_151":311,"_153":312},"NVIDIA NIM","nimmcro_nvidia_nim",{"_155":313,"_150":310},"feature","nvidia_nim","1.7.0-variant",{"_222":1432,"_224":1433},"ngcApps",[1385],"csaApiBaseUrl","https://www.nvidia.com/ai-agents/csa-agent/dcsm","datadogRum",{"_1366":1367,"_1368":1369,"_1370":1371,"_1372":1373,"_1374":326,"_254":352,"_1375":1376,"_1377":51,"_1378":124,"_1379":124,"_1380":1381,"_1382":124,"_1383":1384},"amplitude",{"_1363":1364,"_987":-7,"_1365":26},"disableJs","environment","prod","featureFlagsBlob","JTdCJTIydGVzdEZsYWclMjIlM0FmYWxzZSUyQyUyMnNob3dTZWFyY2hMYWJlbFNldEZpbHRlcnMlMjIlM0FmYWxzZSUyQyUyMmVuYWJsZUNzYVdpZGdldCUyMiUzQWZhbHNlJTJDJTIyY29udGFpbmVyU2Nhbm5pbmdSZWRlc2lnbk0yJTIyJTNBdHJ1ZSU3RA==","featureFlagsGuarded","isDevLikeEnv","isPlaywright","isMobileDevice","categorizedOrgs",{"_1357":1358,"_1359":1360,"_1361":1362},"currentOrgContext","currentContextRoles",[],"enterpriseOrgs",[],"manageableExternalUserGroups",[],"ngcApiOrigin","ngcHelmOrigin","origin","https://catalog.ngc.nvidia.com","usesMocks","theme","year",2026,"now",1794623107653,"1.31.0","defaultSearchSuggestions",{"_1257":433,"_1258":1259,"_1260":1261,"_1262":1263},"announcements",[],"consentState",{"_389":1247,"_1248":26,"_1249":26,"_1250":124,"_1251":1252},"consentConfig",{"_371":372,"_373":374,"_375":376,"_377":378,"_379":380,"_381":382,"_383":384,"_385":386,"_387":388,"_389":390},"showContactAdmin",[],[],[365,366,367,368,369,370],{"_40":62,"_42":68,"_44":64,"_46":-5,"_48":-5,"_50":51},{"_40":62,"_42":65,"_44":64,"_46":-5,"_48":-5,"_50":51},{"_40":55,"_42":60,"_44":64,"_46":-5,"_48":-5,"_50":51},{"_40":55,"_42":56,"_44":64,"_46":-5,"_48":-5,"_50":51},{"_40":52,"_42":53,"_44":64,"_46":-5,"_48":-5,"_50":51},{"_40":41,"_42":43,"_44":45,"_46":47,"_48":54,"_50":51},"mainInfoText","We and our third-party partners (including social media, advertising, and analytics partners) use cookies and other tracking technologies to collect, store, monitor, and process certain information about you when you visit our website. 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