Stay organized with collections
Save and categorize content based on your preferences.
Vertex AI on Google Distributed Cloud (GDC) air-gapped appliance brings the power of a
machine learning (ML) and artificial intelligence (AI) platform to your secure
portable device. GDC air-gapped appliance provides access to a select set of
pre-trained Vertex AI APIs, enabling AI capabilities in your private
cloud solution.
Key features
Vertex AI on GDC air-gapped appliance offers you the following features:
Air-gapped deployment: Run Vertex AI services entirely within
your portable device, ensuring data sovereignty and compliance.
Familiar Vertex AI experience: Take advantage of the same tools
and APIs from Google Cloud, simplifying development and management.
Pre-built models and algorithms: Access a range of pre-trained models
for common machine learning tasks, accelerating your time to value.
Available services
Vertex AI on GDC air-gapped appliance offers the following pre-trained
services:
Each Vertex AI service requires different computing resources. The
following table provides the requirements for each pre-trained model:
Pre-trained API
Computing resources
GPU count requirements
GPU memory requirements
Optical Character Recognition (OCR)
GPU
A single A100 80 GB GPU
40 GB
Speech-to-Text
CPU
Not applicable (only CPU)
Not applicable (only CPU)
Vertex AI Translation
GPU
A single A100 80 GB GPU
50 GB
GDC air-gapped appliance includes a single NVIDIA A100 80 GB GPU. This
limits the device to running only one GPU-dependent Vertex AI
pre-trained API at a time. If you attempt to enable both Vertex AI Translation
and OCR, the second API will fail to enable with an error
message indicating insufficient GPU resources. You can, however, run
Speech-to-Text alongside either Vertex AI Translation or OCR,
as Speech-to-Text only requires CPU resources.
To help you determine the number of appliance units needed for your AI/ML
workloads, review the following capacity limits for each Vertex AI
pre-trained API:
Pre-trained API
Capacity per appliance unit
Optical Character Recognition (OCR)
Up to 30 images per minute (one image every two seconds).
Speech-to-Text
Up to seven minutes of audio transcribed per minute (seven seconds of audio transcribed per second).
Vertex AI Translation
Up to 61,000 characters per minute (1,024 characters per second).
When you plan your deployment, consider the following guidance:
The capacity limits are approximate and not guaranteed. Actual capacity might
vary depending on factors such as the following:
Complexity of the input data (for example, language for translation, image
quality for OCR, and audio clarity for Speech-to-Text).
Specific configuration of the appliance.
Concurrent usage of other services on the appliance.
Only one GPU-intensive API (Vertex AI Translation or OCR) can
be active at a time because GDC air-gapped appliance is limited to a single
A100 80 GB GPU.
Estimate your peak usage and potential future growth.
The following table outlines the storage requirements for each
Vertex AI service on GDC air-gapped appliance:
Component
Storage requirements
OCR frontend
0.1 GB
OCR backend
5 GB
OCR extractor
0.1 GB
Speech-to-Text frontend
0.1 GB
Speech-to-Text backend
1.5 GB
Vertex AI Translation frontend
0.7 GB
Vertex AI Translation backend
61.4 GB
Ensure that your appliance has sufficient storage capacity to accommodate the
Vertex AI services you intend to use.
Benefits
Vertex AI on GDC air-gapped appliance offers the following benefits:
Seamless development experience: Use the same tools, APIs, and workflows
of Vertex AI on Google Cloud, making development and management
intuitive and efficient.
Enhanced security and privacy: Maintain complete control over your data
and comply with regulatory requirements.
Accelerated time to value: Use pre-trained models for common machine
learning tasks.
Streamlined MLOps: Benefit from robust machine learning operation
capabilities for seamless AI integrations within your air-gapped
environment.
Getting started
To get started with Vertex AI on GDC air-gapped appliance, do the
following:
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-09-04 UTC."],[],[],null,["# Vertex AI overview\n\nVertex AI on Google Distributed Cloud (GDC) air-gapped appliance brings the power of a\nmachine learning (ML) and artificial intelligence (AI) platform to your secure\nportable device. GDC air-gapped appliance provides access to a select set of\npre-trained Vertex AI APIs, enabling AI capabilities in your private\ncloud solution.\n\nKey features\n------------\n\nVertex AI on GDC air-gapped appliance offers you the following features:\n\n- **Air-gapped deployment**: Run Vertex AI services entirely within your portable device, ensuring data sovereignty and compliance.\n- **Familiar Vertex AI experience**: Take advantage of the same tools and APIs from Google Cloud, simplifying development and management.\n- **Pre-built models and algorithms**: Access a range of pre-trained models for common machine learning tasks, accelerating your time to value.\n\nAvailable services\n------------------\n\nVertex AI on GDC air-gapped appliance offers the following pre-trained\nservices:\n\n- [**Optical Character Recognition (OCR)**](/distributed-cloud/hosted/docs/latest/appliance/application/ao-user/vertex-ai-ocr): Extract text from images and files.\n- [**Speech-to-Text**](/distributed-cloud/hosted/docs/latest/appliance/application/ao-user/vertex-ai-stt): Convert spoken language into written text.\n- [**Vertex AI Translation**](/distributed-cloud/hosted/docs/latest/appliance/application/ao-user/vertex-ai-translation): Translate text between multiple languages.\n\n| **Caution:** GDC air-gapped appliance includes a single NVIDIA A100 80 GB GPU. This limits the device to running only *one* GPU-dependent Vertex AI pre-trained API at a time. For more information, see [Capacity planning and computing requirements](#capacity).\n\nCapacity planning and computing requirements\n--------------------------------------------\n\nEach Vertex AI service requires different computing resources. The\nfollowing table provides the requirements for each pre-trained model:\n\nGDC air-gapped appliance includes a single NVIDIA A100 80 GB GPU. This\nlimits the device to running only *one* GPU-dependent Vertex AI\npre-trained API at a time. If you attempt to enable both Vertex AI Translation\nand OCR, the second API will fail to enable with an error\nmessage indicating insufficient GPU resources. You can, however, run\nSpeech-to-Text alongside either Vertex AI Translation or OCR,\nas Speech-to-Text only requires CPU resources.\n\nTo help you determine the number of appliance units needed for your AI/ML\nworkloads, review the following capacity limits for each Vertex AI\npre-trained API:\n\nWhen you plan your deployment, consider the following guidance:\n\n- The capacity limits are approximate and not guaranteed. Actual capacity might\n vary depending on factors such as the following:\n\n - Complexity of the input data (for example, language for translation, image quality for OCR, and audio clarity for Speech-to-Text).\n - Specific configuration of the appliance.\n - Concurrent usage of other services on the appliance.\n- Only one GPU-intensive API (Vertex AI Translation or OCR) can\n be active at a time because GDC air-gapped appliance is limited to a single\n A100 80 GB GPU.\n\n- Estimate your peak usage and potential future growth.\n\n- For demanding workloads requiring higher throughput, consider deploying\n multiple appliance units.\n\nThe following table outlines the storage requirements for each\nVertex AI service on GDC air-gapped appliance:\n\nEnsure that your appliance has sufficient storage capacity to accommodate the\nVertex AI services you intend to use.\n\nBenefits\n--------\n\nVertex AI on GDC air-gapped appliance offers the following benefits:\n\n- **Seamless development experience**: Use the same tools, APIs, and workflows of Vertex AI on Google Cloud, making development and management intuitive and efficient.\n- **Enhanced security and privacy**: Maintain complete control over your data and comply with regulatory requirements.\n- **Accelerated time to value**: Use pre-trained models for common machine learning tasks.\n- **Streamlined MLOps**: Benefit from robust machine learning operation capabilities for seamless AI integrations within your air-gapped environment.\n\nGetting started\n---------------\n\nTo get started with Vertex AI on GDC air-gapped appliance, do the\nfollowing:\n\n- [Learn about essential roles and permissions for available services](/distributed-cloud/hosted/docs/latest/appliance/application/ao-user/vertex-ai-ao-permissions).\n- [Set up a project for your AI and machine learning workloads](/distributed-cloud/hosted/docs/latest/appliance/application/ao-user/vertex-ai-set-up-project).\n- [Provision GPUs and enable the Vertex AI services](/distributed-cloud/hosted/docs/latest/appliance/application/ao-user/vertex-ai-enable-pre-trained-apis).\n- [Install the Vertex AI client libraries](/distributed-cloud/hosted/docs/latest/appliance/application/ao-user/vertex-ai-install-libraries)."]]