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FLUX.1-Kontext Container Overview

Description:

This container houses FLUX.1 Kontext [dev] model which is a 12 billion parameter rectified flow transformer capable of editing images based on text instructions.
\nKey Features::
\nChange existing images based on an edit instruction.\nHave character, style and object reference without any finetuning.\nRobust consistency allows users to refine an image through multiple successive edits with minimal visual drift.\nTrained using guidance distillation, making FLUX.1 Kontext [dev] more efficient.\nOpen weights to drive new scientific research, and empower artists to develop innovative workflows.\nGenerated outputs can be used for personal, scientific, and commercial purposes, as described in the FLUX.1 [dev] Non-Commercial License.

The container components are ready for non-commercial use. Contact sales@blackforestlabs.ai for commercial terms to use the Flux.1-Kontext-dev model.

Third-Party Community Consideration:

This model 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:

black-forest-labs/FLUX.1-Kontext-dev Model Card

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 and use of the Cosmos model is governed by NVIDIA Open Model License Agreement. Contact sales@blackforestlabs.ai for commercial terms to use the Flux.1-Kontext-dev model. ADDITIONAL INFORMATION: Llama 2 Community Model License Agreement. and Apache License, Version 2.0.

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

Deployment Geography:

Global

Release Date:

build.nvidia.com August 11, 2025 via https://build.nvidia.com/black-forest-labs/flux_1-kontext-dev
Huggingface June 26, 2025 via https://huggingface.co/black-forest-labs/FLUX.1-Kontext-dev

FLUX.1-Kontext:

The FLUX.1-Kontext 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
FLUX.1-Kontext	Change existing images based on an edit instruction, Have character, style and object reference without any finetuning.	Automatic

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.

References

Flux.1-Kontext-dev blog post

Container Version(s):

nvcr.io/nim/black-forest-labs/flux.1-kontext-dev:latest

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.

Users are responsible for model inputs and outputs. Users are responsible for ensuring safe integration of this model, including implementing guardrails as well as other safety mechanisms, prior to deployment.

Please report 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 Visual Generative AI NIM page for release documentation, deployment guides and more.

NVIDIA Developer Community Forum

For support, Visit the NVIDIA Developer Community Forum

End of Support — \"This artifact is no longer supported. NVIDIA strongly recommends artifacts that are up to date and supported\"

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\nKey Features::
\nChange existing images based on an edit instruction.\nHave character, style and object reference without any finetuning.\nRobust consistency allows users to refine an image through multiple successive edits with minimal visual drift.\nTrained using guidance distillation, making FLUX.1 Kontext [dev] more efficient.\nOpen weights to drive new scientific research, and empower artists to develop innovative workflows.\nGenerated outputs can be used for personal, scientific, and commercial purposes, as described in the FLUX.1 [dev] Non-Commercial License.\n\nThe container components are ready for non-commercial use. Contact sales@blackforestlabs.ai for commercial terms to use the Flux.1-Kontext-dev model.\n\n## Third-Party Community Consideration:\nThis model 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:\n* [black-forest-labs/FLUX.1-Kontext-dev Model Card](https://huggingface.co/black-forest-labs/FLUX.1-Kontext-dev)\n\n### License/Terms of Use:\nGOVERNING 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/) and use of the Cosmos model is governed by [NVIDIA Open Model License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/). Contact sales@blackforestlabs.ai for commercial terms to use the Flux.1-Kontext-dev model. ADDITIONAL INFORMATION: [Llama 2 Community Model License Agreement](https://github.com/meta-llama/llama-models/blob/main/models/llama2/LICENSE). and [Apache License, Version 2.0](https://huggingface.co/datasets/choosealicense/licenses/blob/main/markdown/apache-2.0.md).\n\n**You 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* build.nvidia.com August 11, 2025 via [https://build.nvidia.com/black-forest-labs/flux_1-kontext-dev](https://build.nvidia.com/black-forest-labs/flux_1-kontext-dev)\n* Huggingface June 26, 2025 via https://huggingface.co/black-forest-labs/FLUX.1-Kontext-dev
\n\n## FLUX.1-Kontext:
\nThe FLUX.1-Kontext Container includes the following model:\n\n| Model Name & Link | Use Case | How to Pull the Model |\n|---------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------|-----------------------|\n| [FLUX.1-Kontext](https://build.nvidia.com/black-forest-labs/flux_1-kontext-dev) | Change existing images based on an edit instruction, Have character, style and object reference without any finetuning. | Automatic |\n\n\n## Deployment Details:
\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## References\n\n* [Flux.1-Kontext-dev blog post](https://bfl.ai/announcements/flux-1-kontext/)\n\n## Container Version(s): \nnvcr.io/nim/black-forest-labs/flux.1-kontext-dev:latest \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## 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 this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse. \n\nUsers are responsible for model inputs and outputs. Users are responsible for ensuring safe integration of this model, including implementing guardrails as well as other safety mechanisms, prior to deployment.\n\nPlease report 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\nDeploying and integrating the NIM is straightforward thanks to our industry standard APIs. Visit the [Visual Generative AI NIM page](https://docs.nvidia.com/nim/visual-genai/latest/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/)\n\n**End of Support** — \"This artifact is no longer supported. NVIDIA strongly recommends artifacts that are up to date and supported\"","displayName","FLUX.1-Kontext",["D",1781561598923],"publisher","NVIDIA","latestVersion","versions",[217,211,209,207,162,205,213,203,215,200],"imageUrl","/api/image/nim/black-forest-labs/containers/flux.1-kontext-dev","rawImageUrl","canGuestDownload","latestVersionSizeInBytes",10608732692,"licenseTerms","isMultinodeEnabled","isMultiArchitecture","hasSignedTag","featureLabels",[275],"displayLabels",[268,269],"policyLabels",[],"systemLabels",[260],"products",[],"hasNimMetadata",{"_231":261,"_262":261,"_263":264,"_265":266},"signed images","value","filter",{"_267":266,"_262":261},"category","system","field",{"_231":273,"_262":273,"_263":274,"_265":272},{"_231":270,"_262":270,"_263":271,"_265":272},"NSPECT-UKQM-71BF",{"_267":272,"_262":270},"label","Experimental",{"_267":272,"_262":273},{"_231":276,"_262":277,"_263":278,"_265":279},"NVIDIA NIM","nimmcro_nvidia_nim",{"_267":280,"_262":277},"feature","nvidia_nim",{"_99":1258,"_101":1259},"ngcApps",[1211],"csaApiBaseUrl","https://www.nvidia.com/ai-agents/csa-agent/dcsm","datadogRum",{"_1192":1193,"_1194":1195,"_1196":1197,"_1198":1199,"_1200":292,"_131":318,"_1201":1202,"_1203":51,"_1204":78,"_1205":78,"_1206":1207,"_1208":78,"_1209":1210},"amplitude",{"_1189":1190,"_832":-7,"_1191":26},"disableJs","environment","prod","featureFlagsBlob","JTdCJTIydGVzdEZsYWclMjIlM0FmYWxzZSUyQyUyMnNob3dTZWFyY2hMYWJlbFNldEZpbHRlcnMlMjIlM0FmYWxzZSUyQyUyMmVuYWJsZUNzYVdpZGdldCUyMiUzQWZhbHNlJTJDJTIyZW5hYmxlUHJvZHVjdEdyb3VwaW5nQnlTdWJzY3JpcHRpb24lMjIlM0FmYWxzZSUyQyUyMmNvbnRhaW5lclNjYW5uaW5nUmVkZXNpZ25NMiUyMiUzQWZhbHNlJTdE","featureFlagsGuarded","isDevLikeEnv","isPlaywright","isMobileDevice","categorizedOrgs",{"_1183":1184,"_1185":1186,"_1187":1188},"currentOrgContext","currentContextRoles",[],"enterpriseOrgs",[],"manageableExternalUserGroups",[],"ngcApiOrigin","ngcHelmOrigin","origin","https://catalog.ngc.nvidia.com","usesMocks","theme","year",2026,"now",1787750806097,"1.12.0","defaultSearchSuggestions",{"_1072":399,"_1073":1074,"_1075":1076,"_1077":1078},"announcements",[],"consentState",{"_356":1062,"_1063":78,"_1064":26,"_1065":26,"_1066":1067},"consentConfig",{"_338":339,"_340":341,"_342":343,"_344":345,"_346":347,"_348":349,"_350":351,"_352":353,"_354":355,"_356":357},"showContactAdmin",1787750806098,[],[],[332,333,334,335,336,337],{"_40":61,"_42":66,"_44":63,"_46":-5,"_48":-5,"_50":51},{"_40":61,"_42":64,"_44":63,"_46":-5,"_48":-5,"_50":51},{"_40":54,"_42":59,"_44":63,"_46":-5,"_48":-5,"_50":51},{"_40":54,"_42":55,"_44":63,"_46":-5,"_48":-5,"_50":51},{"_40":52,"_42":53,"_44":63,"_46":-5,"_48":-5,"_50":51},{"_40":41,"_42":43,"_44":63,"_46":-5,"_48":-5,"_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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These cookies may store a unique ID so that our system will remember you when you return. 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