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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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Mistral Large 3 675B Instruct Container Overview

Description:

This container houses the Mistral Large 3 675B Instruct 2512 model which is a state-of-the-art general-purpose multimodal granular Mixture-of-Experts model with 41B active parameters and 675B total parameters, trained from the ground up with 3000 H200s. This instruct post-trained version in FP8 precision is fine-tuned for instruction tasks, making it ideal for chat, agentic, and instruction-based use cases. Designed for reliability and long-context comprehension, it is engineered for production-grade assistants, retrieval-augmented systems, scientific workloads, and complex enterprise workflows.

The container components are ready for commercial use.

License/Terms of Use:

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

Huggingface 12/05/2025 via link
build.nvidia.com 12/05/2025 via link

Mistral Large 3 675B Instruct NIM:

The Mistral Large 3 675B Instruct Container includes the Mistral Large 3 675B Instruct 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	Use Case	How to Pull the Model
Mistral Large 3 675B Instruct	Ideal for chat, agentic, and instruction-based use cases.	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.

\nVisit the NVIDIA NIM for Cosmos page for release documentation, deployment guides and more.

Container Version(s):

nvcr.io/nim/mistralai/mistral-large-3-675b-instruct-2512:1.6.0

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.

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 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 mistral-large-3-675b-instruct-2512 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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\n\nThe container components are ready for commercial use.
\n\n\n### License/Terms of Use:\nGOVERNING TERMS: Use of this NIM 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/). 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/). Additional Information: [Apache License Version 2.0](https://www.apache.org/licenses/LICENSE-2.0.txt).\n\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* Huggingface 12/05/2025 via [link ](https://huggingface.co/mistralai/Mistral-Large-3-675B-Instruct-2512 )\n* build.nvidia.com 12/05/2025 via [link ](https://build.nvidia.com/mistralai/mistral-large-3-675b-instruct-2512 )\n\n\n## Mistral Large 3 675B Instruct NIM:
\nThe Mistral Large 3 675B Instruct Container includes the Mistral Large 3 675B Instruct model.\n| Model Name | Use Case | How to Pull the Model |\n|---|---|---|\n| Mistral Large 3 675B Instruct | Ideal for chat, agentic, and instruction-based use cases.| Automatic |\n\n\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.
\nVisit the NVIDIA NIM for Cosmos [page](https://docs.nvidia.com/nim/vision-language-models/latest/introduction.html) for release documentation, deployment guides and more.
\n\n\n## Container Version(s): \nnvcr.io/nim/mistralai/mistral-large-3-675b-instruct-2512:1.6.0\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\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 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 [mistral-large-3-675b-instruct-2512 NIM page](https://docs.nvidia.com/nim/vision-language-models/latest/introduction.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",["D",1770945535615],"publisher","Mistral AI","latestVersion","versions",[169,206,204,201],"imageUrl","/api/image/nim/mistralai/containers/mistral-large-3-675b-instruct-2512","rawImageUrl","canGuestDownload","latestVersionSizeInBytes",10368228260,"licenseTerms",{"_267":268,"_269":16,"_270":271,"_272":20,"_273":274},"isMultinodeEnabled","isMultiArchitecture","hasSignedTag","featureLabels",[261],"displayLabels",[255,256],"policyLabels",[],"systemLabels",[248],"products",[],"hasNimMetadata",{"_219":249,"_250":249,"_251":252,"_75":253},"signed images","value","filter",{"_254":253,"_250":249},"system","field",{"_219":259,"_250":259,"_251":260,"_75":81},{"_219":257,"_250":257,"_251":258,"_75":81},"NSPECT-OJJU-9FXA",{"_254":81,"_250":257},"Experimental",{"_254":81,"_250":259},{"_219":262,"_250":263,"_251":264,"_75":265},"NVIDIA NIM","nimmcro_nvidia_nim",{"_254":266,"_250":263},"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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It helps track your activity on the platform, including how you interact with their embedded services on other websites.","C0003","Personalization Cookies","These cookies collect data about how you have interacted with our website to help us improve your web experience, such as which pages you have visited. These cookies may store a unique ID so that our system will remember you when you return. They may be set by us or by third party providers whose services we have added to our pages. 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. If you do not allow these cookies, then some or all of these services may not function properly.",[588,589,590,591,592,593,594,595,596,597,598,599,600,601,602,603,604,605,606,607,608,609,610,611,612],[559,560,561,562,563],{"_397":473,"_219":473,"_170":399,"_370":583},{"_397":447,"_219":447,"_170":399,"_370":578},{"_397":573,"_219":573,"_170":399,"_370":574},{"_397":568,"_219":568,"_170":399,"_370":569},{"_397":564,"_219":564,"_170":399,"_370":565},"nvidia.partners",[566],{"_202":567,"_404":564,"_405":20,"_170":441},"edge","app.hushly.com",[570],{"_202":571,"_404":568,"_405":20,"_170":572},"*CORS","This domain is associated with Hushly, a platform that provides lead conversion solutions for content marketing by using personalization and content engagement strategies.","github.com",[575],{"_202":576,"_404":573,"_405":20,"_170":577},"_octo","This domain is owned by Github. 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These cookies may store a unique ID so that our system will remember you when you return. Information collected with these cookies is used to measure and find ways to improve website performance.",[671,672,673,674,675,676,677,678,679,680,681,682,683,684,685,686,687,688,689,690,691,692,693,694,695,696,697,698,699],[651,652,653,654],{"_397":666,"_219":666,"_170":399,"_370":667},{"_397":661,"_219":661,"_170":399,"_370":662},{"_397":460,"_219":460,"_170":399,"_370":658},{"_397":573,"_219":573,"_170":399,"_370":655},[656],{"_202":657,"_404":573,"_405":18,"_170":577},"_gh_sess",[659],{"_202":660,"_404":460,"_405":18,"_170":467},"YSC","bizible.com",[663],{"_202":664,"_404":661,"_405":20,"_170":665},"_BUID","Bizible is a marketing attribution software that tracks the performance of marketing efforts and connects them to revenue, primarily used for B2B environments.","a.usbrowserspeed.com",[668],{"_202":669,"_404":666,"_405":20,"_170":670},"tuid","This domain is owned by Ookla which provides internet speed testing services through its Speedtest application.",{"_202":741,"_404":519,"_405":20,"_170":742},{"_202":726,"_404":740,"_405":18,"_170":727},{"_202":709,"_404":522,"_405":20,"_170":634},{"_202":709,"_404":622,"_405":20,"_170":634},{"_202":738,"_404":519,"_405":20,"_170":739},{"_202":726,"_404":525,"_405":18,"_170":727},{"_202":736,"_404":519,"_405":20,"_170":737},{"_202":726,"_404":522,"_405":18,"_170":727},{"_202":734,"_404":621,"_405":20,"_170":735},{"_202":726,"_404":643,"_405":18,"_170":727},{"_202":706,"_404":522,"_405":20,"_170":708},{"_202":732,"_404":519,"_405":18,"_170":733},{"_202":730,"_404":519,"_405":20,"_170":731},{"_202":728,"_404":519,"_405":18,"_170":729},{"_202":726,"_404":617,"_405":18,"_170":727},{"_202":724,"_404":519,"_405":20,"_170":725},{"_202":722,"_404":519,"_405":20,"_170":723},{"_202":720,"_404":519,"_405":18,"_170":721},{"_202":718,"_404":626,"_405":20,"_170":719},{"_202":706,"_404":617,"_405":20,"_170":708},{"_202":716,"_404":519,"_405":20,"_170":717},{"_202":714,"_404":519,"_405":18,"_170":715},{"_202":712,"_404":519,"_405":20,"_170":713},{"_202":710,"_404":519,"_405":20,"_170":711},{"_202":709,"_404":519,"_405":20,"_170":634},{"_202":706,"_404":707,"_405":20,"_170":708},{"_202":704,"_404":519,"_405":20,"_170":705},{"_202":702,"_404":519,"_405":18,"_170":703},{"_202":700,"_404":519,"_405":20,"_170":701},"_ga_xxxxxxxxxx","Used by Google Analytics to identify and track an individual session with your device.","s_ppvl","This cookie is set by Adobe Analytics to store information on the percentage of the page displayed to the end user.","coveo_visitorId","This cookie name is associated with Coveo which is used to store a unique user ID for marketing purposes and to track the number of distinct users who submitted a query or clicked an item, counting them only once even if they did the same query or clicked the same item over the course of many visits.","_dd_s","marketplace.nvidia.com","Datadog Cookie used to group all events generated from a unique user session across multiple pages. 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