FLUX.2 klein 4B Container Overview

Description:

This container houses Flux.2 [klein] 4B, which is the fastest Black Forest Labs image model to date. FLUX.2 [klein] unifies generation and editing in a single compact architecture, delivering state-of-the-art quality with end-to-end inference in as low as under a second. FLUX.2 [klein] 4B is a 4 billion parameter rectified flow transformer capable of generating images from text descriptions and supports multi-reference editing capabilities.

The container components are ready for commercial/non-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:

black-forest-labs/FLUX.2-klein-4B 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. The Flux.2 Klein 4B model is available at https://huggingface.co/black-forest-labs/FLUX.2-klein-4B. Use of the Cosmos Guardrail model is governed by 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:

build.nvidia.com March 12, 2025 via https://build.nvidia.com/black-forest-labs/flux_2-klein-4b
HuggingFace January 15, 2026 via https://huggingface.co/black-forest-labs/FLUX.2-klein-4B

FLUX.2-klein-4B:

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.2-klein-4B	Text-to-image generation and multi-reference image editing (inpainting, style transfer, object manipulation) with low-latency inference	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.2-Klein blog post

Container Version(s):

nvcr.io/nim/black-forest-labs/flux.2-klein-4b:latest

Key Considerations:

The models embedded in this container can generate synthetic images and may produce content that is inaccurate, offensive, or otherwise inappropriate. Users should implement robust safety guardrails — including content filtering, abuse monitoring, and access controls— to reduce the risk of harmful outputs. Users are responsible for ensuring that their use of the model complies with all applicable laws and regulations, and for regularly reviewing and updating their guardrails as risks evolve.

For more information about the implementation of Cosmos pre and post guardrails to improve model safety, please see the Cosmos-1.0 Guardrail Model.

For more information about Black Forest Labs' pre-training and post-training mitigations to improve model safety, please visit the Responsible AI Development section at this link.

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 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.

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 model 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 Visual Generative AI NIM 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/)

Enterprise Support

Get access to knowledge base articles and support cases or submit a ticket.

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\n\nGlobal\n\n### Release Date: \n\n* build.nvidia.com March 12, 2025 via [https://build.nvidia.com/black-forest-labs/flux_2-klein-4b](https://build.nvidia.com/black-forest-labs/flux_2-klein-4b) \n* HuggingFace January 15, 2026 via [https://huggingface.co/black-forest-labs/FLUX.2-klein-4B](https://huggingface.co/black-forest-labs/FLUX.2-klein-4B) \n\n\n## FLUX.2-klein-4B:
\nThe FLUX.1-Kontext Container includes the following model:\n\n| Model Name & Link | Use Case | How to Pull the Model |\n|-----------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------|-----------------------|\n| [FLUX.2-klein-4B](https://huggingface.co/black-forest-labs/FLUX.2-klein-4B) | Text-to-image generation and multi-reference image editing (inpainting, style transfer, object manipulation) with low-latency inference | 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.2-Klein blog post](https://bfl.ai/blog/flux2-klein-towards-interactive-visual-intelligence)\n\n## Container Version(s): \nnvcr.io/nim/black-forest-labs/flux.2-klein-4b:latest \n\n## Key Considerations:\n\nThe models embedded in this container can generate synthetic images and may produce content that is inaccurate, offensive, or otherwise inappropriate. Users should implement robust safety guardrails — including content filtering, abuse monitoring, and access controls— to reduce the risk of harmful outputs. Users are responsible for ensuring that their use of the model complies with all applicable laws and regulations, and for regularly reviewing and updating their guardrails as risks evolve.\n\nFor more information about the implementation of Cosmos pre and post guardrails to improve model safety, please see the [Cosmos-1.0 Guardrail Model](https://huggingface.co/nvidia/Cosmos-1.0-Guardrail).\n\nFor more information about Black Forest Labs' pre-training and post-training mitigations to improve model safety, please visit the Responsible AI Development section at [this link](https://huggingface.co/black-forest-labs/FLUX.2-klein-4B).\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 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\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\n Please report model 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\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\nGet access to community knowledge base articles and support cases (https://forums.developer.nvidia.com/)\n\n## Enterprise Support\nGet access to knowledge base articles and support cases or [submit a ticket](https://www.nvidia.com/en-us/data-center/products/ai-enterprise-suite/support/).","FLUX.2-klein-4B",["D",1791846559736],[293,289,287,285,283,211,291,280],"/api/image/nim/black-forest-labs/containers/flux.2-klein-4b",19616047077,{"_334":335,"_336":337,"_338":339,"_340":26},"hasSignedTag",[325,326],[321],[],[313],[],{"_91":314,"_315":314,"_316":317,"_318":319},"signed images","value","filter",{"_320":319,"_315":314},"category","system","field",{"_91":322,"_315":322,"_316":323,"_318":324},"NSPECT-RSXS-GQAU",{"_320":324,"_315":322},"label",{"_91":332,"_315":332,"_316":333,"_318":330},{"_91":327,"_315":328,"_316":329,"_318":330},"NVIDIA NIM","nimmcro_nvidia_nim",{"_320":331,"_315":328},"feature","nvidia_nim","NVIDIA AI Enterprise Supported",{"_320":324,"_315":332},"governingTerms","

GOVERNING TERMS:The NIM container is governed by theNVIDIA Software License AgreementandProduct-Specific Terms for NVIDIA AI Products.The Flux.2 Klein model is available athttps://huggingface.co/black-forest-labs/FLUX.2-klein-4B.Use of the NVIDIA Cosmos-1.0 Guardrail is governed by theNVIDIA Open Model License Agreement.ADDITIONAL INFORMATION:Apache 2.0license.

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It is set after visitors have seen a cookie information notice and in some cases only when they actively close the notice down. It enables the website not to show the message more than once to a user. The cookie has a normal lifespan of one year and contains no personal information.","This cookie is associated with Akamai and is used to differentiate between traffic from humans and bots.","omniverse.nvidia.com","The __cf_bm cookie is a cookie necessary to support Cloudflare Bot Management, currently in private beta. As part of our bot management service, this cookie helps manage incoming traffic that matches criteria associated with bots.\nThis is a CloudFoundry cookie","OptanonConsent","nvid.nvidia.com","This cookie is set by the cookie compliance solution from OneTrust. It stores information about the categories of cookies the site uses and whether visitors have given or withdrawn consent for the use of each category. 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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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