The CREATE MODEL statement for Gemini Enterprise Agent Platform LLMs as MaaS

This document describes the CREATE MODEL statement for creating remote models in BigQuery over LLMs in Gemini Enterprise Agent Platform as a model as a service (MaaS) by using SQL. When you use MaaS on Agent Platform, you don't have to provision or manage serving infrastructure for your models. Choose MaaS for rapid development and prototyping, when you want to minimize operational overhead. Agent Platform offers access to Google models, partner models and open models using MaaS. For more information, see When to use MaaS.

Alternatively, you can use the Google Cloud console user interface to create a model by using a UI (Preview) instead of constructing the SQL statement yourself.

After you create the remote model, you can use one of the following functions to perform generative AI with that model:

• AI.GENERATE_TEXT
• AI.GENERATE_TABLE (only for Gemini models)

CREATE MODEL syntax

{CREATE MODEL | CREATE MODEL IF NOT EXISTS | CREATE OR REPLACE MODEL}
`project_id.dataset.model_name`
REMOTE WITH CONNECTION {DEFAULT | `project_id.region.connection_id`}
OPTIONS(ENDPOINT = 'vertex_ai_llm_endpoint');

CREATE MODEL

Creates and trains a new model in the specified dataset. If the model name exists, CREATE MODEL returns an error.

CREATE MODEL IF NOT EXISTS

Creates and trains a new model only if the model doesn't exist in the specified dataset.

CREATE OR REPLACE MODEL

Creates and trains a model and replaces an existing model with the same name in the specified dataset.

model_name

The name of the model you're creating or replacing. The model name must be unique in the dataset: no other model or table can have the same name. The model name must follow the same naming rules as a BigQuery table. A model name can:

• Contain up to 1,024 characters
• Contain letters (upper or lower case), numbers, and underscores

model_name is case-sensitive.

If you don't have a default project configured, then you must prepend the project ID to the model name in the following format, including backticks:

`[PROJECT_ID].[DATASET].[MODEL]`

For example, `myproject.mydataset.mymodel`.

REMOTE WITH CONNECTION

Syntax

`[PROJECT_ID].[LOCATION].[CONNECTION_ID]`

BigQuery uses a Cloud resource connection to interact with the Gemini Enterprise Agent Platform endpoint.

The connection elements are as follows:

• PROJECT_ID: the project ID of the project that contains the connection.
• LOCATION: the location used by the connection. The connection must be in the same location as the dataset that contains the model.
• CONNECTION_ID: the connection IDfor example, myconnection.

  To find your connection ID, view the connection details in the Google Cloud console. The connection ID is the value in the last section of the fully qualified connection ID that is shown in Connection IDfor example projects/myproject/locations/connection_location/connections/myconnection.

  To use a default connection, specify DEFAULT instead of the connection string containing PROJECT_ID.LOCATION.CONNECTION_ID.

If you are using the remote model to analyze unstructured data from an object table, you must also grant the Vertex AI Service Agent role to the service account of the connection associated with the object table. You can find the object table's connection in the Google Cloud console, on the Details pane for the object table.

Example

`myproject.us.my_connection`

ENDPOINT

Syntax

ENDPOINT = 'vertex_ai_llm_endpoint'

Description

The Agent Platform endpoint for the remote model to use. You can specify the name of the Agent Platform model, for example gemini-2.5-pro, or you can specify the Agent Platform model's endpoint URL, for example https://europe-west6-aiplatform.googleapis.com/v1/projects/myproject/locations/europe-west6/publishers/google/models/gemini-2.5-pro. If you specify the model name, BigQuery ML automatically identifies and uses the full endpoint of the Agent Platform model based on the location of the dataset in which you create the model.

Arguments

A STRING value that contains the model name of the target Agent Platform LLM. The following LLMs are supported:

  https://aiplatform.googleapis.com/v1/projects/test-project/locations/global/publishers/google/models/gemini-2.5-pro

For information that can help you choose between the supported models, see Model information.

Locations

For information about supported locations, see Locations for remote models.

Examples

The following examples create BigQuery ML remote models.

Create a Gemini model that uses the default connection

The following example creates a BigQuery ML remote model over a Gemini model:

CREATE OR REPLACE MODEL `mydataset.gemini_model`
REMOTE WITH CONNECTION DEFAULT
OPTIONS(ENDPOINT = 'gemini-2.5-pro');

Create a partner model that uses the default connection

The following example creates a BigQuery ML remote model over a Mistral AI model:

CREATE OR REPLACE MODEL `mydataset.mistral_model`
REMOTE WITH CONNECTION DEFAULT
OPTIONS(ENDPOINT = 'mistral-large-2411');

What's next

• For more information about using Agent Platform models with BigQuery ML, see Generative AI overview.
• Try generating text from BigQuery data.
• Try generating structured text from BigQuery data.