Google 是业界首家发布 AI/机器学习隐私权承诺的公司，该承诺概述了客户应拥有最高级别安全性并能够控制其在云中存储的数据的这一信念。该承诺会延伸到 Google Cloud的生成式 AI 产品。Google 通过健全的数据治理实践（包括审核 Google Cloud 在其产品开发中使用的数据），确保 Google 团队遵循这些承诺。如需详细了解 Google 如何处理数据，另请参阅 Google 的云端数据处理附录 (CDPA)。
在以下情形和条件下，客户数据会在 Vertex AI 中保留一段时间，以供 Google 模型使用。若要实现零数据保留，客户必须在以下各个方面采取特定措施：
Google 模型的数据缓存：默认情况下，Google 基础模型会缓存 Gemini 模型的输入和输出。这样做是为了减少延迟时间，并加快对客户后续提示的回答速度。缓存的内容最多可在处理请求的数据中心存储 24 小时。数据缓存功能在 Google Cloud 项目级启用或停用，系统会对缓存的数据强制提供项目级隐私保护。 Google Cloud 项目的相同缓存设置适用于所有区域。如要实现零数据保留，您必须停用数据缓存。请参阅启用和停用数据缓存。
使用 Google 搜索建立依据：如服务专用条款第 19 条“生成式 AI 服务：使用 Google 搜索建立依据”中所述，Google 会存储客户可能提供的提示和上下文信息，并将生成的输出内容保存三十 (30) 天，以用于创建有依据的结果和搜索建议。这些存储的信息还可用于调试和测试支持使用 Google 搜索建立依据的系统。如果您使用“使用 Google 搜索建立依据”功能，则无法禁止存储此类信息。
可信测试员计划：如果您之前选择加入该计划，按可信测试员计划条款允许 Google 使用您的数据来改进非正式 AI/机器学习服务，Google 可能会保留您的数据。如需退出此计划，请参阅选择退出可信测试人员计划。
启用和停用数据缓存
您可以使用以下 curl 命令来获取缓存状态、停用缓存或重新启用缓存。
停用或重新启用缓存时，更改将应用于所有 Google Cloud 区域。如需详细了解如何使用 Identity and Access Management 授予启用或停用缓存所需的权限，请参阅使用 IAM 进行 Vertex AI 访问权限控制。展开以下部分，了解如何获取当前缓存设置、停用缓存以及启用缓存。
[[["易于理解","easyToUnderstand","thumb-up"],["解决了我的问题","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["很难理解","hardToUnderstand","thumb-down"],["信息或示例代码不正确","incorrectInformationOrSampleCode","thumb-down"],["没有我需要的信息/示例","missingTheInformationSamplesINeed","thumb-down"],["翻译问题","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["最后更新时间 (UTC)：2025-08-28。"],[],[],null,["# Generative AI and zero data retention\n\nGoogle was the first in the industry to publish an\n[AI/ML Privacy Commitment](https://cloud.google.com/blog/products/ai-machine-learning/google-cloud-unveils-ai-and-ml-privacy-commitment),\nwhich outlines our belief that customers should have the highest level of\nsecurity and control over their data that is stored in the cloud. That commitment\nextends to Google Cloud's generative AI products. Google ensures that its\nteams are following these commitments through robust data governance practices,\nwhich include reviews of the data that Google Cloud uses in the development of\nits products. More details about how Google processes data can also be found in\nGoogle's [Cloud Data Processing Addendum (CDPA)](https://cloud.google.com/terms/data-processing-addendum).\n\nTraining restriction\n--------------------\n\nAs outlined in Section 17 \"Training Restriction\" in the Service Terms section of\n[Service Specific Terms](https://cloud.google.com/terms/service-terms),\nGoogle won't use your data to train or fine-tune any AI/ML models without your\nprior permission or instruction. This applies to all managed models on\nVertex AI, including GA and pre-GA models.\n\nCustomer data retention and achieving zero data retention\n---------------------------------------------------------\n\nCustomer data is retained in Vertex AI for Google models for limited\nperiods of time in the following scenarios and conditions. To achieve zero data retention, customers must take specific actions within each of these areas:\n\n- **Data caching for Google models** : By default, Google foundation models cache inputs for Gemini models. This is done to reduce latency and accelerate responses to subsequent prompts from the customer. Cached contents are stored for up to 24 hours in the data center where the request was served. Data caching is enabled or disabled at the Google Cloud project level, and project-level privacy is enforced for cached data. The same cache settings for a Google Cloud project apply to all regions. To achieve zero data retention, you must disable data caching. See [Enabling and disabling data caching](#enabling-disabling-caching).\n- **Prompt logging for abuse monitoring for Google models** : As outlined in Section 4.3 \"Generative AI Safety and Abuse\" of [Google Cloud Platform Terms of Service](https://cloud.google.com/terms), Google may log prompts to detect potential abuse and violations of its [Acceptable Use Policy](https://cloud.google.com/terms/aup) and [Prohibited Use Policy](https://policies.google.com/terms/generative-ai/use-policy) as part of providing generative AI services to customers. Only customers whose use of Google Cloud is governed by the [Google Cloud Platform Terms of Service](https://cloud.google.com/terms) and who don't have an [Invoiced Cloud Billing account](/billing/docs/concepts#billing_account_types) are subject to prompt logging for abuse monitoring. If you are in scope for prompt logging for abuse monitoring and want zero data retention, you can request an exception for abuse monitoring. See [Abuse monitoring](/vertex-ai/generative-ai/docs/learn/abuse-monitoring).\n- **Grounding with Google Search** : As outlined in Section 19 \"Generative AI Services: Grounding with Google Search\" of the [Service Specific Terms](https://cloud.google.com/terms/service-terms), Google stores prompts and contextual information that customers may provide, and generated output for thirty (30) days for the purposes of creating grounded results and search suggestions, and this stored information may be used for debugging and testing of systems that support grounding with Google Search. There is no way to disable the storage of this information if you use Grounding with Google Search.\n- **Session resumption for Gemini Live API:** This feature is disabled by default. It must be enabled by the user every time they call the API by specifying the field in the API request, and project-level privacy is enforced for cached data. Enabling Session Resumption allows the user to reconnect to a previous session within 24 hours by storing cached data, including text, video, and audio prompt data and model outputs, for up to 24 hours. To achieve zero data retention, do not enable this feature. For more information about this feature, including how to enable it, see [Live API](/vertex-ai/generative-ai/docs/live-api#session-resumption).\n\nThis applies to all managed models on Vertex AI, including GA and\npre-GA models.\n\n### Enabling and disabling data caching\n\nYou can use the following curl commands to get\ncaching status, disable caching, or re-enable caching.\nWhen you disable or re-enable caching, the change\napplies to all Google Cloud regions. For more information about using\nIdentity and Access Management to grant permissions required to enable or disable caching, see\n[Vertex AI access control with IAM](/vertex-ai/docs/general/access-control).\nExpand the following sections to learn how to get the current cache setting, to\ndisable caching, and to enable caching. \n\n#### Get current caching setting\n\nRun the following command to determine if caching is enabled or disabled for a\nproject. To run this command, a user must be granted one of the following\nroles: `roles/aiplatform.viewer`, `roles/aiplatform.user`, or\n`roles/aiplatform.admin`. \n\n```\nPROJECT_ID=PROJECT_ID\n# Setup project_id\n$ gcloud config set project PROJECT_ID\n\n# GetCacheConfig\n$ curl -X GET -H \"Authorization: Bearer $(gcloud auth application-default print-access-token)\" -H \"Content-Type: application/json\" https://us-central1-aiplatform.googleapis.com/v1/projects/PROJECT_ID/cacheConfig\n\n# Response if caching is enabled (caching is enabled by default).\n{\n \"name\": \"projects/PROJECT_ID/cacheConfig\"\n}\n\n# Response if caching is disabled.\n{\n \"name\": \"projects/PROJECT_ID/cacheConfig\"\n \"disableCache\": true\n}\n \n``` \n\n#### Disable caching\n\nRun the following curl command to disable caching for a Google Cloud project. To run\nthis command, a user must be granted the Vertex AI administrator role,\n`roles/aiplatform.admin`. \n\n```\nPROJECT_ID=PROJECT_ID\n# Setup project_id\n$ gcloud config set project PROJECT_ID\n\n# Setup project_id.\n$ gcloud config set project ${PROJECT_ID}\n\n# Opt-out of caching.\n$ curl -X PATCH -H \"Authorization: Bearer $(gcloud auth application-default print-access-token)\" -H \"Content-Type: application/json\" https://us-central1-aiplatform.googleapis.com/v1/projects/PROJECT_ID/cacheConfig -d '{\n \"name\": \"projects/PROJECT_ID/cacheConfig\",\n \"disableCache\": true\n}'\n\n# Response.\n{\n \"name\": \"projects/PROJECT_ID/locations/us-central1/projects/PROJECT_ID/cacheConfig/operations/${OPERATION_ID}\",\n \"done\": true,\n \"response\": {\n \"@type\": \"type.googleapis.com/google.protobuf.Empty\"\n }\n}\n \n``` \n\n#### Enable caching\n\nIf you disabled caching for a Google Cloud project and want re-enable it, run the\nfollowing curl command. To run this command, a user must be granted the\nVertex AI administrator role, `roles/aiplatform.admin`. \n\n```\nPROJECT_ID=PROJECT_ID\nLOCATION_ID=\"us-central1\"\n# Setup project_id\n$ gcloud config set project PROJECT_ID\n\n# Setup project_id.\n$ gcloud config set project ${PROJECT_ID}\n\n# Opt in to caching.\n$ curl -X PATCH -H \"Authorization: Bearer $(gcloud auth application-default print-access-token)\" -H \"Content-Type: application/json\" https://us-central1-aiplatform.googleapis.com/v1/projects/PROJECT_ID/cacheConfig -d '{\n \"name\": \"projects/PROJECT_ID/cacheConfig\",\n \"disableCache\": false\n}'\n\n# Response.\n{\n \"name\": \"projects/PROJECT_ID/locations/us-central1/projects/PROJECT_ID/cacheConfig/operations/${OPERATION_NUMBER}\",\n \"done\": true,\n \"response\": {\n \"@type\": \"type.googleapis.com/google.protobuf.Empty\"\n }\n}\n \n```\n\nWhat's next\n-----------\n\n- Learn about [responsible AI best practices and Vertex AI's safety filters](/vertex-ai/generative-ai/docs/learn/responsible-ai).\n- Learn about [Gemini in Google Cloud data governance](/gemini/docs/discover/data-governance)."]]
