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GOVERNING DOWNLOAD TERMS: Use of the model is governed by the NVIDIA Open Model Agreement.

ADDITIONAL INFORMATION: Apache License, Version 2.0.

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Inkling

Description

Inkling is a general-purpose multimodal autoregressive transformer model from Thinking Machines Lab Inc. that accepts text, image, and audio inputs and generates text outputs. The model is intended for English and other languages, multiple coding languages, agentic and tool-use systems, coding assistants, chatbots, retrieval-augmented generation systems, general-purpose conversational use, instruction following, and other natural language or multimodal tasks.

This model is ready for commercial or non-commercial use.

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 Non-NVIDIA Inkling Model Card

License and Terms of Use:

**GOVERNING TERMS: Use of the model is governed by the NVIDIA Open Model Agreement. ADDITIONAL INFORMATION: Apache License, Version 2.0.

Deployment Geography:

Global

Use Case:

Use Case: Inkling is intended for developers building AI-powered applications, including agentic and tool-use systems, coding assistants, chatbots, retrieval-augmented generation systems, general-purpose conversational AI, instruction-following systems, and multimodal applications.

Release Date:

Build.NVIDIA.com: 07/15/2026 via link\nHuggingface: 07/15/2026 via link

Reference(s):

References:

Model Architecture:

Architecture Type: Transformer\nNetwork Architecture: Mixture-of-Experts\nTotal Parameters: 975B\nActive Parameters: 41B

Input:

Input Types: Text, Image, Audio\nInput Formats: String, Red, Green, Blue (RGB), Other (Waveform)\nInput Parameters: One-Dimensional (1D), Two-Dimensional (2D), One-Dimensional (1D)\nOther Input Properties: Text input uses UTF-8 encoding; image input supports pixel-based formats with each dimension ideally between 40 and 4,096 pixels; audio input uses WAV format sampled at 16 kHz and is ideally under 20 minutes.

Output:

Output Types: Text\nOutput Format: String\nOutput Parameters: One-Dimensional (1D)\nOther Output Properties: Inkling generates UTF-8 encoded text.

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.

Software Integration:

Runtime Engines:

SGLang
vLLM

Supported Hardware:

NVIDIA Blackwell: B300
NVIDIA Hopper: H200

Preferred Operating Systems: Linux

The integration of foundation and fine-tuned models into AI systems requires additional testing using use-case-specific data to ensure safe and effective deployment. Following the V-model methodology, iterative testing and validation at both unit and system levels are essential to mitigate risks, meet technical and functional requirements, and ensure compliance with safety and ethical standards before deployment.

Model Version(s)

Inkling v1.0

Training, Testing, and Evaluation Datasets:

Training Dataset

Data Modality: Text, Image, Audio, Video\nText Training Data Size: Undisclosed\nImage Training Data Size: Undisclosed\nAudio Training Data Size: Undisclosed\nVideo Training Data Size: Undisclosed\nTraining Data Collection: Hybrid: Automated, Manually-Collected, Synthetic\nTraining Labeling: Undisclosed\nTraining Properties: Training data includes a broad variety of content types, including text, images, audio, and video, drawn from publicly available sources, third-party acquired sources, and synthetically generated or augmented data. The training data curation process includes cleaning, processing, modification, deduplication, filtering, and other data-type-specific processing steps to remove low-quality content or advance safety objectives.

Testing Dataset

Testing Data Collection: Undisclosed\nTesting Labeling: Undisclosed\nTesting Properties: Undisclosed

Evaluation Dataset

Evaluation Benchmark Score: Inkling reports reasoning, agentic, factuality, chat, vision, audio, and safety benchmark results at effort=0.99. Selected official Hugging Face scores include 46.0% HLE with tools, 97.1% AIME 2026, 77.6% SWEBench Verified, 54.3% SWEBench Pro (Public), 63.8 Terminal Bench 2.1, 88.7% Global-MMLU-Lite, 73.3% MMMU Pro (Standard 10), 91.4% VoiceBench, and 98.6% StrongREJECT.

Detailed benchmark comparison tables are available in the official Inkling Model Card.

Evaluation Data Collection: Hybrid: Automated, Manually-Collected\nEvaluation Labeling: Hybrid: Automated, Manually-Labeled\nEvaluation Properties: The evaluation suite covers reasoning, coding and agentic tasks, factuality, chat and instruction following, multimodal vision and audio tasks, and safety benchmarks, with results reported at effort=0.99 and comparison scores from the r/acc leaderboard generated July 14, 2026.

Inference

Acceleration Engine: SGLang + Dynamo\nTest Hardware: NVIDIA Blackwell (GB200)

Additional Details

Inkling may exhibit general limitations common to foundation models, including hallucination, occasional failures to follow instructions precisely, degraded performance in long multi-turn conversations, demographic, cultural, or linguistic bias, and uneven performance across languages, dialects, or subject domains that were less represented during training. Downstream developers and deployers should apply human oversight for high-stakes or safety-critical contexts, conduct use-case-specific evaluation, and implement application-layer safeguards such as content filtering, rate limiting, monitoring, and input/output moderation.

Safety evaluations were conducted ahead of release across everyday human-AI interaction and dangerous-capability testing. Evaluation areas included sycophancy, harmful manipulation, psychological-harm patterns, refusal behavior, CBRN, cyber, loss of control, agentic capability, strategic deception, sabotage potential, internal evaluations, external testing, open-ended external red teaming, and refusal-suppressed variants to estimate latent capability with safeguards removed. For more information on model safety, please view the Inkling Model Card.

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. Developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse.

Please make sure you have proper rights and permissions for all input image content; if image includes people, personal health information, or intellectual property, the image generated will not blur or maintain proportions of image subjects included.

Please report model quality, risk, security vulnerabilities or NVIDIA AI Concerns here.

Get Help

NVIDIA Developer Community Forum

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

","resourceVersions",[158,159],"resourceVersionsTotal",1,"hasMoreVersions","versionMetadata",{"_129":130,"_131":132,"_41":133,"_134":-5,"_135":136,"_137":138,"_139":140,"_141":142,"_143":16,"_144":-5,"_145":18,"_146":-5,"_147":18,"_148":-5,"_149":18,"_150":-5,"_151":18,"_152":-5,"_153":18,"_154":-5,"_155":18,"_156":157},"versionNotFound","isLoggedIn","latestVersionPath","/orgs/nim/thinkingmachines/models/inkling/-","version","-","imageReference","cliDownloadCommand","ngc registry model download-version nim/thinkingmachines/inkling:nvfp4-1.3","helmFetchCommand","viewAllVersionsPath","/orgs/nim/thinkingmachines/models/inkling/-/version-history","accessCheckResult",{"_128":16},"hasRelatedCollections","context",{"_124":125,"_126":127},1784313730494,[],[],[117,118,119,120,121,122],{"_37":52,"_39":61,"_41":54,"_43":55,"_45":62,"_47":48},{"_37":52,"_39":59,"_41":54,"_43":55,"_45":60,"_47":48},{"_37":52,"_39":57,"_41":54,"_43":55,"_45":123,"_47":48},{"_37":52,"_39":53,"_41":54,"_43":55,"_45":56,"_47":48},{"_37":49,"_39":50,"_41":42,"_43":44,"_45":51,"_47":48},{"_37":38,"_39":40,"_41":42,"_43":44,"_45":46,"_47":48},58,"orgName","nim","teamName","thinkingmachines","allowed","versionId","nvfp4-1.3","description","","UPLOAD_COMPLETE","releaseType","createdDate",["D",1784156628978],"updatedDate",["D",1784156710454],"totalSizeInBytes",612305052565,"totalFileCount",47,"isSigned","malwareScanStatus","isScanned","releaseNotes","hasReleaseNotes","setup","hasSetup","quickStartGuide","hasQuickStartGuide","advanced","hasAdvanced","performance","hasPerformance","policies",[],{"_160":101,"_161":163,"_134":-5,"_143":16,"_145":18,"_156":162,"_147":18},{"_160":130,"_161":130,"_134":-5,"_143":16,"_145":18,"_156":162,"_147":18},"id","name",[],"Latest (nvfp4-1.3)","nim/thinkingmachines/inkling","nim/thinkingmachines/models/inkling","resourceType","models","resourceId","inkling","shortDescription","Inkling is a general-purpose multimodal autoregressive transformer model from Thinking Machines Lab Inc. that accepts text, image, and audio inputs and generates text outputs.","# Inkling\n\n## Description\nInkling is a general-purpose multimodal autoregressive transformer model from Thinking Machines Lab Inc. that accepts text, image, and audio inputs and generates text outputs. The model is intended for English and other languages, multiple coding languages, agentic and tool-use systems, coding assistants, chatbots, retrieval-augmented generation systems, general-purpose conversational use, instruction following, and other natural language or multimodal tasks.\n\n*This model is ready for commercial or non-commercial use.*\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 Non-NVIDIA [Inkling Model Card](https://huggingface.co/thinkingmachines/Inkling)\n\n## License and Terms of Use:\n**GOVERNING TERMS: Use of the model is governed by the [NVIDIA Open Model Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-agreement/). ADDITIONAL INFORMATION: [Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0).\n\n## Deployment Geography:\nGlobal\n\n## Use Case:\n**Use Case:** Inkling is intended for developers building AI-powered applications, including agentic and tool-use systems, coding assistants, chatbots, retrieval-augmented generation systems, general-purpose conversational AI, instruction-following systems, and multimodal applications.\n\n## Release Date:\n**Build.NVIDIA.com:** 07/15/2026 via [link](http://build.nvidia.com/thinkingmachines/inkling)\n**Huggingface:** 07/15/2026 via [link](https://huggingface.co/thinkingmachines/Inkling)\n\n## Reference(s):\n**References:**\n- [Inkling Model Page](https://huggingface.co/thinkingmachines/Inkling)\n- [Inkling NVFP4 Model Page](https://huggingface.co/thinkingmachines/Inkling-NVFP4)\n- [Thinking Machines Acceptable Use Policy](https://thinkingmachines.ai/model-acceptable-use-policy/)\n- [Tinker Cookbook](https://github.com/thinking-machines-lab/tinker-cookbook)\n- [Inkling Tinker Documentation](https://tinker-docs.thinkingmachines.ai/cookbook/inkling/)\n\n## Model Architecture:\n**Architecture Type:** Transformer\n**Network Architecture:** Mixture-of-Experts\n**Total Parameters:** 975B\n**Active Parameters:** 41B\n\n### Input:\n**Input Types:** Text, Image, Audio\n**Input Formats:** String, Red, Green, Blue (RGB), Other (Waveform)\n**Input Parameters:** One-Dimensional (1D), Two-Dimensional (2D), One-Dimensional (1D)\n**Other Input Properties:** Text input uses UTF-8 encoding; image input supports pixel-based formats with each dimension ideally between 40 and 4,096 pixels; audio input uses WAV format sampled at 16 kHz and is ideally under 20 minutes.\n\n### Output:\n**Output Types:** Text\n**Output Format:** String\n**Output Parameters:** One-Dimensional (1D)\n**Other Output Properties:** Inkling generates UTF-8 encoded text.\n\n__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.__\n\n## Software Integration:\n**Runtime Engines:**\n- **SGLang**\n- **vLLM**\n\n**Supported Hardware:**\n- **NVIDIA Blackwell:** B300\n- **NVIDIA Hopper:** H200\n\n**Preferred Operating Systems:** Linux\n\n__The integration of foundation and fine-tuned models into AI systems requires additional testing using use-case-specific data to ensure safe and effective deployment. Following the V-model methodology, iterative testing and validation at both unit and system levels are essential to mitigate risks, meet technical and functional requirements, and ensure compliance with safety and ethical standards before deployment.__\n\n## Model Version(s)\nInkling v1.0\n\n## Training, Testing, and Evaluation Datasets:\n\n### Training Dataset\n**Data Modality:** Text, Image, Audio, Video\n**Text Training Data Size:** Undisclosed\n**Image Training Data Size:** Undisclosed\n**Audio Training Data Size:** Undisclosed\n**Video Training Data Size:** Undisclosed\n**Training Data Collection:** Hybrid: Automated, Manually-Collected, Synthetic\n**Training Labeling:** Undisclosed\n**Training Properties:** Training data includes a broad variety of content types, including text, images, audio, and video, drawn from publicly available sources, third-party acquired sources, and synthetically generated or augmented data. The training data curation process includes cleaning, processing, modification, deduplication, filtering, and other data-type-specific processing steps to remove low-quality content or advance safety objectives.\n\n### Testing Dataset\n**Testing Data Collection:** Undisclosed\n**Testing Labeling:** Undisclosed\n**Testing Properties:** Undisclosed\n\n### Evaluation Dataset\n**Evaluation Benchmark Score:** Inkling reports reasoning, agentic, factuality, chat, vision, audio, and safety benchmark results at effort=0.99. Selected official Hugging Face scores include 46.0% HLE with tools, 97.1% AIME 2026, 77.6% SWEBench Verified, 54.3% SWEBench Pro (Public), 63.8 Terminal Bench 2.1, 88.7% Global-MMLU-Lite, 73.3% MMMU Pro (Standard 10), 91.4% VoiceBench, and 98.6% StrongREJECT.\n\nDetailed benchmark comparison tables are available in the official [Inkling Model Card](https://huggingface.co/thinkingmachines/Inkling).\n\n**Evaluation Data Collection:** Hybrid: Automated, Manually-Collected\n**Evaluation Labeling:** Hybrid: Automated, Manually-Labeled\n**Evaluation Properties:** The evaluation suite covers reasoning, coding and agentic tasks, factuality, chat and instruction following, multimodal vision and audio tasks, and safety benchmarks, with results reported at effort=0.99 and comparison scores from the r/acc leaderboard generated July 14, 2026.\n\n## Inference\n**Acceleration Engine:** SGLang + Dynamo\n**Test Hardware:** NVIDIA Blackwell (GB200)\n\n## Additional Details\nInkling may exhibit general limitations common to foundation models, including hallucination, occasional failures to follow instructions precisely, degraded performance in long multi-turn conversations, demographic, cultural, or linguistic bias, and uneven performance across languages, dialects, or subject domains that were less represented during training. Downstream developers and deployers should apply human oversight for high-stakes or safety-critical contexts, conduct use-case-specific evaluation, and implement application-layer safeguards such as content filtering, rate limiting, monitoring, and input/output moderation.\n\nSafety evaluations were conducted ahead of release across everyday human-AI interaction and dangerous-capability testing. Evaluation areas included sycophancy, harmful manipulation, psychological-harm patterns, refusal behavior, CBRN, cyber, loss of control, agentic capability, strategic deception, sabotage potential, internal evaluations, external testing, open-ended external red teaming, and refusal-suppressed variants to estimate latent capability with safeguards removed. For more information on model safety, please view the [Inkling Model Card](https://huggingface.co/thinkingmachines/Inkling).\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. Developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse.\n\nPlease make sure you have proper rights and permissions for all input image content; if image includes people, personal health information, or intellectual property, the image generated will not blur or maintain proportions of image subjects included.\n\nPlease 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### NVIDIA Developer Community Forum\nGet access to community knowledge base articles and support cases (https://forums.developer.nvidia.com/)","displayName","Inkling",["D",1784156710460],"publisher","Thinking Machines Lab","latestVersion","versions","collectionCounts","imageUrl","/api/image/nim/thinkingmachines/models/inkling","rawImageUrl","canGuestDownload","latestVersionSizeInBytes","licenseTerms",{"_220":221,"_222":14,"_223":224,"_225":18,"_226":227},"isMultinodeEnabled","isMultiArchitecture","bias","explainability","privacy","safetyAndSecurity","featureLabels",[214],"displayLabels",[205,206],"policyLabels",[],"systemLabels",[],"products",[],"hasNimMetadata",{"_173":212,"_208":212,"_209":213,"_72":78},{"_173":207,"_208":207,"_209":210,"_72":78},"NSPECT-AS16-OTEF","value","filter",{"_211":78,"_208":207},"field","False",{"_211":78,"_208":212},{"_173":215,"_208":216,"_209":217,"_72":218},"NVIDIA NIM","nimmcro_nvidia_nim",{"_211":219,"_208":216},"feature","nvidia_nim","governingTerms","

GOVERNING DOWNLOAD TERMS: Use of the model is governed by the NVIDIA Open Model Agreement.

ADDITIONAL INFORMATION: Apache License, Version 2.0.

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We and our advertising partners will use this information to make our websites and the advertising displayed on it, more relevant to your interests.",5,[462,463,464,465,466,467,468,469,470,471,472,473,474,475,476,477,478,479,480,481,482,483,484,485,486,487,488,489,490,491,492,493,494,495,496],[335,336,337,338,339,340,341,342,343,344,345,346,347,348,349,350,351],{"_352":458,"_173":458,"_131":132,"_325":459},{"_352":453,"_173":453,"_131":132,"_325":454},{"_352":449,"_173":449,"_131":132,"_325":450},{"_352":444,"_173":444,"_131":132,"_325":445},{"_352":439,"_173":439,"_131":132,"_325":440},{"_352":427,"_173":427,"_131":132,"_325":428},{"_352":415,"_173":415,"_131":132,"_325":416},{"_352":410,"_173":410,"_131":132,"_325":411},{"_352":399,"_173":399,"_131":132,"_325":400},{"_352":394,"_173":394,"_131":132,"_325":395},{"_352":389,"_173":389,"_131":132,"_325":390},{"_352":384,"_173":384,"_131":132,"_325":385},{"_352":379,"_173":379,"_131":132,"_325":380},{"_352":374,"_173":374,"_131":132,"_325":375},{"_352":369,"_173":369,"_131":132,"_325":370},{"_352":362,"_173":362,"_131":132,"_325":363},{"_352":353,"_173":353,"_131":132,"_325":354},"hostName","amazon-adsystem.com",[355,356],{"_161":361,"_358":353,"_359":18,"_131":360},{"_161":357,"_358":353,"_359":18,"_131":360},"ad-privacy","host","isSession","This domain is owned by online retailer Amazon and is used as part of its affiliate marketing programme.","ad-id","doubleclick.net",[364,365],{"_161":368,"_358":362,"_359":18,"_131":367},{"_161":366,"_358":362,"_359":18,"_131":367},"IDE","This domain is owned by Doubleclick (Google). The main business activity is: Doubleclick is Googles real time bidding advertising exchange","test_cookie","bing.com",[371],{"_161":372,"_358":369,"_359":18,"_131":373},"MUID","This domain is owned by Mircosoft - it is the site for the search engine Bing.","assets.adobedtm.com",[376],{"_161":377,"_358":374,"_359":18,"_131":378},"kndctr_F207D74D549850760A4C98C6_AdobeOrg_consent","If you know anything about this host and its uses please add your contributions here. ","tiktok.com",[381],{"_161":382,"_358":379,"_359":18,"_131":383},"_ttp","TikTok is a social media platform owned by ByteDance, known for short-form video sharing. The service is used to create and share videos, and it utilizes cookies for various purposes including advertising and analytics.","t.co",[386],{"_161":387,"_358":384,"_359":18,"_131":388},"muc_ads","This domain is owned by Twitter. It is used as a URL shortening service, which allows Twitter to collect data on how links are shared.","snowplow.com",[391],{"_161":392,"_358":389,"_359":18,"_131":393},"sp","Testing","google.com",[396],{"_161":397,"_358":394,"_359":18,"_131":398},"NID","This domain is owned by Google Inc. Although Google is primarily known as a search engine, the company provides a diverse range of products and services. Its main source of revenue however is advertising. Google tracks users extensively both through its own products and sites, and the numerous technologies embedded into many millions of websites around the world. It uses the data gathered from most of these services to profile the interests of web users and sell advertising space to organisations based on such interest profiles as well as aligning adverts to the content on the pages where its customer's adverts appear.","tags.srv.stackadapt.com",[401,402,403,404],{"_161":409,"_358":399,"_359":18,"_131":406},{"_161":408,"_358":399,"_359":18,"_131":406},{"_161":407,"_358":399,"_359":18,"_131":406},{"_161":405,"_358":399,"_359":18,"_131":406},"sa-user-id-v3","This domain is associated with StackAdapt, a platform for programmatic advertising, which suggests that it is used for targeting and advertising purposes.","sa-user-id","sa-user-id-v2","sa-user-id-v4","linkedin.com",[412],{"_161":413,"_358":410,"_359":18,"_131":414},"bcookie","This domain is owned by LinkedIn, the business networking platform. It typically acts as a third party host where website owners have placed one of its content sharing buttons in their pages, although its content and services can be embedded in other ways. Although such buttons add functionality to the website they are on, cookies are set regardless of whether or not the visitor has an active Linkedin profile, or agreed to their terms and conditions. For this reason it is classified as a primarily tracking/targeting domain.","twitter.com",[417,418,419,420],{"_161":426,"_358":415,"_359":18,"_131":422},{"_161":424,"_358":415,"_359":18,"_131":425},{"_161":423,"_358":415,"_359":18,"_131":422},{"_161":421,"_358":415,"_359":18,"_131":422},"personalization_id","This domain is owned by Twitter. The main business activity is: Social Networking Services. Where twitter acts as a third party host, it collects data through a range of plug-ins and integrations, that is primarily used for tracking and targeting.","guest_id_marketing","guest_id","Twitter does not currently provide information on the use of specific cookies.","guest_id_ads","youtube.com",[429,430,431,432],{"_161":438,"_358":427,"_359":18,"_131":436},{"_161":437,"_358":427,"_359":18,"_131":436},{"_161":435,"_358":427,"_359":18,"_131":436},{"_161":433,"_358":427,"_359":18,"_131":434},"VISITOR_INFO1_LIVE","This cookie is used as a unique identifier to track viewing of videos","__Secure-YNID","YouTube is a Google owned platform for hosting and sharing videos. YouTube collects user data through videos embedded in websites, which is aggregated with profile data from other Google services in order to display targeted advertising to web visitors across a broad range of their own and other websites.","__Secure-YEC","__Secure-ROLLOUT_TOKEN","demdex.net",[441],{"_161":442,"_358":439,"_359":18,"_131":443},"demdex","This cookie helps Adobe Audience Manger perform basic functions such as visitor identification, ID synchronization, segmentation, modeling, reporting, etc.","im-apps.net",[446],{"_161":447,"_358":444,"_359":18,"_131":448},"receive-cookie-deprecation","This domain is owned by im-apps.net which provides information and resources about various instant messaging (IM) applications to help users make informed decisions based on their communication needs.","influ2.com",[451],{"_161":452,"_358":449,"_359":18,"_131":393},"R","6sc.co",[455],{"_161":456,"_358":453,"_359":18,"_131":457},"6suuid","This domain is associated with the company 6Sense Insights, Inc., which provides predictive analytics and account engagement services. 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It stores a unique visitor identifier, and uses an organisation identifier to allow a company to track users across their domains and services.This is a pattern type cookie name associated with Adobe Marketing Cloud. It stores a unique visitor identifier, and uses an organisation identifier.","kndctr_F207D74D549850760A4C98C6_AdobeOrg_identity","_rdt_pn","www.nvidia.com","This cookie name is associated with www.mind.org.uk which is used for marketing purposes.","ai-podcast.nvidia.com","This cookie is used to identify the user's session on the website and is often associated with analytics or personalization.","_gcl_au","Used by Google AdSense for experimenting with advertisement efficiency across websites using their services","_mkto_trk","This cookie is associated with an email marketing service provided by Marketo. This tracking cookie allows a website to link visitor behaviour to the recipient of an email marketing campaign, to measure campaign effectiveness.","_gat_gtag_UA_140825383_2","Google Analytics","_zitok","This cookie name is associated with ZoomInfo which is used to maintain a unique visitor identifier and store Personally Identifiable Information.","_rdt_uuid","This cookie is set by Reddit and is used for tracking the views of embedded videos and performance of the advertisements.","AMP_91bf70adfe","Supports Amplitude product analytics.","This cookie name is associated with StackAdapt Inc. which is used to support the effective management and optimization of digital advertising campaigns by handling information such as visitor actions on websites, visited pages, time spent, page load speed, and more.","build.nvidia.com","kndctr_F207D74D549850760A4C98C6_AdobeOrg_cluster","_cs_nnnnnnnnnnnnn","This is a session cookie. 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It is commonly used for analytics and personalization of content.","marketplace.nvidia.com","AMP_MKTG_92dea1e784","This cookie is typically associated with SnackTools, which is a suite of web applications for creating and sharing multimedia content. It is used to identify a user across sessions and track user activities.","forums.developer.nvidia.com","This cookie is typically associated with the use of Taptap Digital, a company specializing in digital advertising. It is used for tracking and ad personalization purposes.","_tt_enable_cookie","This cookie name is associated with TikTok which is used to collect data about behavior and purchases on the website and to measure the effect of advertising. It is also used to track website activity to help optimize advertising efforts.","AMCV_xxxxxAdobeOrg","This cookie is used to identify a unique visitor for tracking purposes by Adobe Experience Cloud.This is a pattern type cookie name associated with Adobe Marketing Cloud. It stores a unique visitor identifier, and uses an organisation identifier to allow a company to track users across their domains and services.","ttcsid","This cookie name is associated with TikTok which is used to enable TikTok Ads session tracking by assigning a unique session ID to users who click on TikTok ads, allowing for the attribution of user behavior and conversions within the same session.This cookie is associated with TikTok. It helps track your activity on the platform, including how you interact with their embedded services on other websites.","AMP_MKTG_91bf70adfe","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.",[584,585,586,587,588,589,590,591,592,593,594,595,596,597,598,599,600,601,602,603,604],[549,550,551,552,553],{"_352":444,"_173":444,"_131":132,"_325":575},{"_352":410,"_173":410,"_131":132,"_325":570},{"_352":563,"_173":563,"_131":132,"_325":564},{"_352":559,"_173":559,"_131":132,"_325":560},{"_352":554,"_173":554,"_131":132,"_325":555},"nvcrm.my.site.com",[556],{"_161":557,"_358":554,"_359":18,"_131":558},"BrowserId","If you know anything about this cookie and its uses that are not specific to a particular site please add your contributions.","nvidia.partners",[561],{"_161":562,"_358":559,"_359":18,"_131":393},"edge","github.com",[565,566],{"_161":569,"_358":563,"_359":18,"_131":568},{"_161":567,"_358":563,"_359":18,"_131":568},"logged_in","This domain is owned by Github. 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We have categorized it under Functionality because it is necessary for the operation of our affiliate program.","nv.modal.cuda","This cookie name suggests it is related to a modal popup functionality on NVIDIA's website, possibly to remember user preferences or interactions with the modal.","readme_library","docs.api.nvidia.com","_im_ses.1006927","geo_locator","nv.modal.deepstream","openedx-language-preference","learn.nvidia.com","doxygen_width","raytracing-docs.nvidia.com","This cookie is likely used to remember the width preferences of a sidebar or interface element within a documentation platform like Doxygen.","_sfid_eb78","This cookie is categorized as Functionality Cookie.","_im_id.1006927","_hjUserAttributesHash","docs.nvidia.com","This cookie name is associated with Hotjar which is used to know when any user attribute has changed and needs to be updated.","mbox","Cookie set by Adobe SiteCatalyst analytics software - used for measuring the performance of page content using A/B split testing","nv.modal.cudnn","This cookie name suggests it is related to modal popup handling or user interface preferences on NVIDIA's website, specifically for the cuDNN library section.","readme_language","nv.modal.hpc","This cookie name suggests it is related to a modal pop-up on a website, possibly to control the display of a high-priority cookie notice or other important information to the user.","at_check","Used by Adobe Target to check if cookies are enabled/supported on the browser","_biz_uid","This cookie is used to record website and server performance with each visit to the site. The data is aggregated and analyzed; therefore, it remains anonymous upon use.\n","nvHeadless","This cookie is likely used to track if a user is using the site in a 'headless' non-GUI mode, which could be for accessibility reasons or for automated processes.","_biz_nA","C0002","Performance Cookies","These cookies are used to provide quantitative measures of our website visitors, such as the number of times you visit, time on page, your mouse movements, scrolling, clicks and keystroke activity on the websites; other browsing, search, or product research behavior; and what brought you to our site. 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 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