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GOVERNING DOWNLOAD TERMS

The NIM container is governed by theNVIDIA Software License AgreementandProduct-Specific Terms for NVIDIA AI Products. Use of this model is governed by theNVIDIA Open Model License.Additional Information:MIT License.

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MiMo-V2-Flash Overview

Description:

MiMo-V2-Flash is a Mixture-of-Experts (MoE) language model with 309B total parameters and 15B active parameters. Designed for high-speed reasoning and agentic workflows, it utilizes a novel hybrid attention architecture and Multi-Token Prediction (MTP) to achieve state-of-the-art performance while significantly reducing inference costs.

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

Third-Party Community Consideration

The model MiMo-V2-Flash 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 MiMo-V2-Flash.

License/Terms of Use:

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. 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:

Huggingface 12/17/2025 via
\nhttps://huggingface.co/

NGC 4/29/2026 via
\nhttps://catalog.ngc.nvidia.com/models

Program Classes:

The MiMo-V2-Flash Container includes the following models:

\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
MiMo-V2-Flash	MiMo-V2-Flash is a Mixture-of-Experts (MoE) language model with 309B total parameters and 15B active parameters. Designed for high-speed reasoning and agentic workflows, it utilizes a novel hybrid attention architecture and Multi-Token Prediction (MTP) to achieve state-of-the-art performance while significantly reducing inference costs.	Manual

Deployment Details:

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

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.

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

NVIDIA Developer Community Forum

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

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

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\nThe model MiMo-V2-Flash 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 [MiMo-V2-Flash](https://huggingface.co/XiaomiMiMo/MiMo-V2-Flash).\n\n### License/Terms of Use:\nThe 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](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/). **Additional Information**: [MIT License](https://huggingface.co/datasets/choosealicense/licenses/blob/main/markdown/mit.md).\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\nHuggingface 12/17/2025 via \n[https://huggingface.co/](https://huggingface.co/XiaomiMiMo/MiMo-V2-Flash) \n\nNGC 4/29/2026 via \n[https://catalog.ngc.nvidia.com/models](https://catalog.ngc.nvidia.com/mimo-v2-flash)\n\n## Program Classes:
\n\nThe MiMo-V2-Flash Container includes the following models: \n\n| Model Name & Link | Use Case | How to Pull the Model |\n| :---- | :---- | :---- |\n| MiMo-V2-Flash | MiMo-V2-Flash is a Mixture-of-Experts (MoE) language model with 309B total parameters and 15B active parameters. Designed for high-speed reasoning and agentic workflows, it utilizes a novel hybrid attention architecture and Multi-Token Prediction (MTP) to achieve state-of-the-art performance while significantly reducing inference costs. | Manual |\n\n## Deployment Details:
\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\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## 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 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\nDeploying and integrating the NIM is straightforward thanks to our industry standard APIs. Visit the NIM Container page for release documentation, deployment guides and more [the hyperlink](https://docs.nvidia.com/nim/large-language-models/latest/introduction.html).\n\n### NVIDIA Developer Community Forum\nGet access to community knowledge base articles and support cases (https://forums.developer.nvidia.com/)\n\nYou are responsible for ensuring that your use of NVIDIA provided models complies with all applicable laws.saf","displayName","Mimo-V2-Flash (Experimental)",["D",1777467979073],"publisher","Xiaomi","latestVersion","versions",[152,90],"imageUrl","/api/image/nim/xiaomi/containers/mimo-v2-flash-experimental","rawImageUrl","canGuestDownload","latestVersionSizeInBytes",8648956655,"licenseTerms",{"_228":229,"_230":14,"_231":232,"_233":18,"_234":235},"isMultinodeEnabled","isMultiArchitecture","hasSignedTag","featureLabels",[222],"displayLabels",[202,203,204,205,206],"policyLabels",[],"systemLabels",[195],"products",[],"hasNimMetadata",{"_165":196,"_197":196,"_198":199,"_70":200},"signed images","value","filter",{"_201":200,"_197":196},"system","field",{"_165":218,"_197":219,"_198":220,"_70":74},{"_165":216,"_197":216,"_198":217,"_70":74},{"_165":213,"_197":214,"_198":215,"_70":74},{"_165":209,"_197":210,"_198":211,"_70":74},{"_165":207,"_197":207,"_198":208,"_70":74},"NSPECT-RSFI-F2CT",{"_201":74,"_197":207},"Natural Language Understanding","uscs_natural_language_understanding",{"_201":212,"_197":210},"application","Natural Language Processing","uscs_natural_language_processing",{"_201":212,"_197":214},"Experimental",{"_201":74,"_197":216},"AI","soln_ai",{"_201":221,"_197":219},"technology",{"_165":223,"_197":224,"_198":225,"_70":226},"NVIDIA NIM","nimmcro_nvidia_nim",{"_201":227,"_197":224},"feature","nvidia_nim","governingTerms","

GOVERNING DOWNLOAD TERMS

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GOVERNING HOSTING TERMS

[Add container hosting terms here]

Instruction: The following model's nSpect legal request. Please review with the terms above. [Delete this instruction prior to approval]

ADDITIONAL INFORMATION:

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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.

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These cookies enable us to provide enhanced website functionality and personalization as well as make the marketing messages we send to you more relevant to your interests. 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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. 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.","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","Used to apply end-user cookie consent preferences set by our client-side utility.Custom- Short Duration. Unique ID of an Enquiry- used to validate access to case, and load exisiting data.\n","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.","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.","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.","This cookie is associated with Akamai and is used to differentiate between traffic from humans and bots.","OptanonAlertBoxClosed","docs.ngc.nvidia.com","This cookie is set by websites using certain versions of the cookie law compliance solution from OneTrust. 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.","nv_co","__uxq412__ses.88c1","investor.nvidia.com","learn.learn.nvidia.com","This cookie is associated with the Amazon Web Services Elastic Load Balancing functionality for routing client request on the server.","pctrk","Used to count page views by unauthenticated users against license usage.","bm_s","bpazaws52gukakzc__ctrl0_ctl36_uccaptcha","bm_sv","store.nvidia.com","The __cf_bm cookie is a cookie necessary to support Cloudflare Bot Management, currently in private beta. 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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.","_devzone_session","This cookie is likely used to maintain a user session on the website by the server. It is common for session identifiers to be used to keep users logged in and track their interaction with the site during a session.","_cs_c","The cookie is used by Content Square to save the user consent to be tracked.","bm_sz","This cookie is used by Akamai to optimize site performance and security. It is typically associated with the delivery of web content and services.","vcalliance.nvidia.com","ASP.NET_SessionId","General purpose platform session cookie, used by sites written with Microsoft .NET based technologies. 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