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AI Tool
Unlock the Power of Scalable Batch Predictions
Efficiently process large datasets with Google Cloud’s Vertex AI Batch Predictions, where cost meets performance.
Save up to 50% with cost-effective batch inference for non-time-sensitive tasks.Seamlessly integrate with BigQuery and Cloud Storage for streamlined workflows.Support for a wide array of models including Llama, Qwen, and OpenAI gpt-oss.
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overview
What is Vertex AI Batch Predictions?
Vertex AI Batch Predictions is a powerful tool designed to enable large-scale, asynchronous inference for your machine learning models. Ideal for businesses requiring cost-effective processing without the urgency of real-time results.
- Utilize custom-trained and generative AI models.
- Designed especially for data scientists and ML engineers.
- Optimized for business-critical tasks like customer segmentation.
features
Key Features
Vertex AI Batch Predictions includes a wealth of features for enhanced performance and flexibility in your predictive tasks. Customize your batch jobs according to your unique needs.
- Configurable batch size and machine specifications.
- Support for accelerators to boost performance.
- Manage output formats through the Google Cloud console or API.
use_cases
Ideal Use Cases
Whether you're looking to analyze customer data or generate content in bulk, Vertex AI Batch Predictions is tailored to fit various business needs. Discover how it can transform your workflows.
- Periodic analytics and lead scoring.
- Churn analysis and bulk content generation.
- Document classification and offline data annotation.
Frequently Asked Questions
How does Vertex AI Batch Predictions differ from real-time predictions?
Vertex AI Batch Predictions prioritizes cost savings over immediate results, making it ideal for tasks that do not require instant feedback.
What types of data sources can I integrate with batch predictions?
You can use BigQuery or Cloud Storage as input and output sources, enhancing integration with your existing data workflows.
Is Vertex AI Batch Predictions suitable for large datasets?
Yes, it is designed for efficient processing of large datasets while offering enhanced orchestration and resource management.