Choose a natural language processing function

This document provides a comparison of the natural language processing functions available in BigQuery ML, which are ML.GENERATE_TEXT , ML.TRANSLATE , and ML.UNDERSTAND_TEXT . You can use the information in this document to help you decide which function to use in cases where the functions have overlapping capabilities.

At a high level, the difference between these functions is as follows:

ML.GENERATE_TEXT is a good choice for performing customized natural language processing (NLP) tasks at a lower cost. This function offers more language support, faster throughput, and model tuning capability, and also works with multimodal models.
ML.TRANSLATE is a good choice for performing translation-specific NLP tasks where you need to support a high rate of queries per minute.
ML.UNDERSTAND_TEXT is a good choice for performing NLP tasks that are supported by the Cloud Natural Language API.

Function comparison

Use the following table to compare the ML.GENERATE_TEXT , ML.TRANSLATE , and ML.UNDERSTAND_TEXT functions:

ML.GENERATE_TEXT

ML.TRANSLATE

ML.UNDERSTAND_TEXT

Purpose

Perform any NLP task by passing a prompt to a Gemini or partner model or to an open model .

For example, to perform a question answering task, you could provide a prompt similar to CONCAT("What are the key concepts in the following article?: ", article_text) .

Use the Cloud Translation API to perform the following tasks:

Use the Cloud Natural Language API to perform the following tasks:

Billing

Incurs BigQuery ML charges for data processed. For more information, see BigQuery ML pricing .

Incurs Vertex AI charges for calls to the model. If you are using a Gemini 2.0 or greater model, the call is billed at the batch API rate. For more information, see Cost of building and deploying AI models in Vertex AI .

Incurs BigQuery ML charges for data processed. For more information, see BigQuery ML pricing .

Incurs charges for calls to the Cloud Translation API. For more information, see Cloud Translation API pricing .

Incurs BigQuery ML charges for data processed. For more information, see BigQuery ML pricing .

Incurs charges for calls to the Cloud Natural Language API. For more information, see Cloud Natural Language API pricing .

Requests per minute

Not applicable for Gemini models. Between 25 and 60 for partner models. For more information, see Requests per minute limits .

200. For more information, see Cloud AI service functions .

600. For more information, see Cloud AI service functions .

Tokens per minute

Ranges from 8,192 to over 1 million, depending on the model used.

No token limit. However, ML_TRANSLATE does have a 30,000 bytes limit .

100,000 .

Input data

Supports both text and unstructured data from BigQuery standard tables and object tables.

Supports text data from BigQuery standard tables.

Function output

Output can vary for calls to the model, even with the same prompt.

Produces the same output for a given task type for each successful call to the API. The output includes information about the input language.

Produces the same output for a given task type for each successful call to the API. The output includes information about the magnitude of the sentiment for sentiment analysis tasks.

Data context

You can provide data context as part of the prompt you submit.

Not supported.

Supervised tuning

Supervised tuning is supported for some models.

Not supported.

Supported languages

Support varies based on the LLM you choose.

Supports Cloud Translation API languages .

Supports Cloud Natural Language API languages .

Supported regions

Supported in all Generative AI for Vertex AI regions .

Supported in the EU and US multi-regions.