End-to-end user journeys for generative AI models

This document describes the user journeys for BigQuery ML remote models, including the statements and functions that you can use to work with remote models. BigQuery ML offers the following types of remote models:

• Google models and partner models
• Open models
• Cloud AI services
• Custom models deployed to Vertex AI

Remote model user journeys

The following table describes the statements and functions you can use to create, evaluate, and generate data from remote models:

Model category	Model type	Model creation	Evaluation	Inference	Tutorials
Generative AI remote models	Remote model over a Gemini text generation model1	CREATE MODEL	ML.EVALUATE	ML.GENERATE_TEXT AI.GENERATE_TABLE AI.GENERATE2 AI.GENERATE_BOOL2 AI.GENERATE_DOUBLE2 AI.GENERATE_INT2	Generate text using your data Generate structured data using your data Generate text with Gemini and public data Handle quota errors by calling ML.GENERATE_TEXT iteratively Analyze images with a Gemini model Try model tuning using public data Tune a model using your data
	Remote model over a partner text generation model	CREATE MODEL	ML.EVALUATE	ML.GENERATE_TEXT	N/A
	Remote model over an open text generation model	CREATE MODEL	ML.EVALUATE	ML.GENERATE_TEXT	Generate text with Gemma and public data
	Remote model over a Google embedding generation model	CREATE MODEL	N/A	ML.GENERATE_EMBEDDING	Generate text embeddings using your data Generate image embeddings using your data Generate video embeddings using your data Handle quota errors by calling ML.GENERATE_EMBEDDING iteratively Generate and search multimodal embeddings using public data
Cloud AI remote models	Remote model over the Cloud Vision API	CREATE MODEL	N/A	ML.ANNOTATE_IMAGE	Annotate images
	Remote model over the Cloud Translation API	CREATE MODEL	N/A	ML.TRANSLATE	Translate text
	Remote model over the Cloud Natural Language API	CREATE MODEL	N/A	ML.UNDERSTAND_TEXT	Understand text
	Remote model over the Document AI API	CREATE MODEL	N/A	ML.PROCESS_DOCUMENT	Process documents Parse PDFs in a RAG pipeline
	Remote model over the Speech-to-Text API	CREATE MODEL	N/A	ML.TRANSCRIBE	Transcribe audio files
Remote model over a custom model deployed to Vertex AI	Remote model over a custom model deployed to Vertex AI	CREATE MODEL	ML.EVALUATE	ML.PREDICT	Make predictions with a custom model

¹Some Gemini models support supervised tuning.

²This function calls a hosted Gemini model, and doesn't require you to create a model separately using the CREATE MODEL statement.