Exam objective

GAIL

Use cases and strengths of Google's foundation models

This objective sits in Fundamentals of gen AI, which carries 30% of the Generative AI Leader exam. The questions below are original, written from the official objective title above, and each explanation cites the Google Cloud page it rests on.

Objective title verbatim from the official objectives. Google Cloud exam page

A worked example

Shown solved, with the whole explanation open: this is what every question here carries.

Fundamentals of gen AI

A business needs to generate high quality images from text descriptions. Which Google model fits?

ImagenCorrect · your answerCorrect.
VeoVeo produces video clips from prompts.
GemmaGemma targets local deployment, not text to image generation.
Gemini NanoGemini Nano is an on device model, not an image generator.

Correct.

Concept

Imagen is a text to image diffusion model that generates high quality images from text descriptions.

Why A

Generating images from text descriptions is Imagen's stated purpose.

Source

Imagen: It's a text-to-image diffusion model that generates high-quality images from textual descriptions.

Google Cloud, Generative AI Leader study guide, checked August 2026
#google-models

Now you: practice questions

No account needed. The explanation opens when you answer.

Sample question 1 of 3

Fundamentals of gen AI

A studio wants to produce video clips from text prompts or still images. Which Google model applies?

Sample question 2 of 3

Fundamentals of gen AI

A developer wants a user friendly, customizable Google model suited to local deployments. Which model fits?

Sample question 3 of 3

Fundamentals of gen AI

Which Google model supports multimodal understanding, conversational AI, content creation, and question answering?

That’s 3 of the full Generative AI Leader bank.

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Read the sources

These are the official pages the questions above cite. Reading them is studying the objective from the primary source, which is what the explanations point you toward anyway.

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