Overview of models on Agent Platform

The Agent Platform provides access to broad classes of large language models (LLMs) and generative AI models, including Google first-party models, partner models, and open-weights models. This page provides an index of documentation for these models, organized by model types, access options, capabilities, customization, evaluation, and safety.

Get started

Get started with using models on the Agent Platform.

Quickstart

Quickly start calling APIs on the platform.

Get an API key

Learn how to create and manage API keys.

Set up Authentication

Configure application default credentials.

Google GenAI Libraries

Download and install libraries for major programming languages.

Model Garden

Model Garden provides a centralized location to discover, test, and deploy a wide variety of first-party, partner, and open-source models.

Overview of Model Garden

Discover the models available in the catalog.

Use Models in Model Garden

Learn how to interact with and consume models.

Quickstart

Test model capabilities quickly.

Deploy Open Models

Instructions for deploying open models from to endpoints.

Model Types

Agent Platform provides access to a variety of models, including:

Google Models

Flagship models developed by Google, including Gemini, Gemma, Veo, and Lyria.

Partner Models

Models from leading AI providers integrated into the platform, such as Anthropic Claude, Grok, and Mistral AI.

Open Models

Support for a wide range of open-weights models like DeepSeek, Llama, and Qwen.

Model Access and Deployment

Depending on the model and your requirements, you can access models in two ways:

Model as a Service (MaaS)

Use managed APIs for partner and open models without managing infrastructure.

Model Garden

Discover, test, and customize a wide variety of first-party, partner, and open-source models.

Model Capabilities

Explore advanced capabilities supported by the models:

Long Context

Understand how to work with models that support large context windows.

Thinking Models

Learn about models with reasoning and thinking capabilities.

Computer Use

Documentation on models capable of interacting with computer interfaces.

Bounding Box Detection

Detect objects and return coordinates.

Model Customization (Tuning)

Tailor models to your specific needs:

Tune Models Overview

An introduction to model tuning on Agent Platform.

Gemini Supervised Tuning

Fine-tune Gemini models using supervised training.

Gemini Preference Tuning

Align model behavior using human feedback or preference data.

Tune Embeddings

Customize text or multimodal embeddings.

Model Evaluation

Assess model performance objectively:

Evaluation Overview

Learn about the Gen AI evaluation service, including adaptive rubrics.

Run Evaluation

How to execute evaluation jobs.

Evaluation using Console

Guided workflow via the web UI.

Evaluation using SDK

Programmatic evaluation using Python.

Safety & Security

Build responsible AI applications:

Safety Overview

Overview of safety features and content filtering.

Responsible AI

Guidelines and tools for responsible AI usage.

Abuse Monitoring

How abuse monitoring is handled.

Consumption options

Understand the available consumption options:

Flex Pay-as-you-go

Learn about the Flex pricing model.

Priority Pay-as-you-go

Learn about the Priority pricing model.

Standard Pay-as-you-go

Learn about the Standard pricing model.

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.

Last updated 2026年09月01日 UTC.