After it's imported, it becomes a Model resource that is visible in Vertex AI Model Registry. Then, read the following documentation to learn how to get inferences: ... Deploy model to endpoint and get online inferences. Learn about Compute resources for prediction.

May 5, 2025 - Today, we are pleased to announce Vertex AI Prediction Dedicated Endpoints, a new family of Vertex AI Prediction endpoints, designed to address the needs of modern AI applications, including those related with large-scale generative AI models.

You'll also write custom post processing logic to round the predictions and convert them to strings. To write this logic, you'll use custom prediction routines. The Vertex AI pre-built containers handle prediction requests by performing the prediction operation of the machine learning framework.

March 27, 2026 - The predictor is responsible for the ML logic for processing a prediction request, such as custom preprocessing and postprocessing. To write custom prediction logic, you'll subclass the Vertex AI Predictor interface.

March 27, 2026 - In this lab, you'll use Vertex AI to get online and batch predictions from a custom trained model.

"- Upload the TensorFlow estimator model as a `Vertex AI Model` resource.\n", ... "- Make an online raw prediction to the `Model` resource instance deployed to the `Endpoint` resource."

4 days ago - A practical guide to Vertex AI prediction and model monitoring, including batch prediction, online prediction, model serving, skew, drift, and alert thresholds.

April 14, 2026 - Vertex AI Prediction is the Vertex AI service area in Google Cloud that provides managed model inference for: – Online prediction: low-latency, request/response predictions from a deployed endpoint – Batch prediction: high-throughput offline scoring over large datasets using batch jobs

October 3, 2023 - Vertex AI forecasting models now support Probabilistic Inference - an improvement over the “pinball” quantile loss method used in Vertex AI forecasting models until now. Probabilistic inference is based on recent Google research and models the distribution of the prediction target explicitly, offering multiple advantages:

# This client only needs to be created once, and can be reused for multiple requests. client = aiplatform.gapic.PredictionServiceClient(client_options=client_options) instance = json_format.ParseDict(instance_dict, Value()) instances = [instance] parameters_dict = {} parameters = json_format.ParseDict(parameters_dict, Value()) endpoint = client.endpoint_path( project=project, location=location, endpoint=endpoint_id ) response = client.predict( endpoint=endpoint, instances=instances, parameters=parameters ) print("response") print(" deployed_model_id:", response.deployed_model_id) predictions = response.predictions for prediction in predictions: print(" prediction:", dict(prediction))

Forecasting models predict a sequence of values.

November 11, 2025 - Vertex AI offers several primary endpoint types for online prediction, each designed for a specific set of use cases. This document provides a detailed technical deep-dive into each endpoint ...

March 27, 2026 - In this tutorial you’ll learn how to perform baseline testing using HEY and prediction cloud monitoring metrics.

"This tutorial demonstrates how to use Vertex AI LLM for making streaming predictions on large language models.\n",

February 17, 2026 - Batch prediction processes all ... Vertex AI Batch Prediction takes your data from BigQuery or GCS, runs it through your model using multiple machines in parallel, and writes the results back....

September 3, 2024 - Use batch predictions to process accumulated time series data in a single request when immediate response time is not required. Vertex AI makes it simple to go from training machine learning forecasting models like TiDE to deploying them and ...

May 30, 2023 - Google Vertex AI Batch Predictions Batch predictions allow you to predict large amounts of data in parallel. Vertex AI Batch Prediction is made for large datasets that would take too much time with …

Learn how to create text prompts for handling any number of tasks with Agent Platform's generative AI support. Some of the most common tasks are classification, summarization, and extraction. Gemini on Agent Platform lets you design prompts with flexibility in terms of their structure and format. ... When you're ready to use your model to solve a real-world problem, register your model to Model Registry and use the Agent Platform prediction service for batch and online predictions.

"- Set the variable `DEPLOY_COMPUTE` to configure your compute resources for prediction.\n", ... "*Note: You may also use n2 and e2 machine types for training and deployment, but they do not support GPUs*." ... "First, you upload the pre-trained custom tabular model artifacts as a Vertex AI model resource using the `upload()` method, with the following parameters:\n",