Vertex AI Model Optimizer

Vertex AI Model Optimizer is a dynamic endpoint designed to simplify model selection by automatically applying the Gemini model which best meets your needs. This lets you point your prompts at a single meta-endpoint and the service intelligently selects the most appropriate Gemini model for your query (Pro, Flash, etc.) based on your cost and quality preferences.

For more information on Model Optimizer pricing, see Pricing.

Benefits

Model Optimizer lets you:

• Simplify your model selection rather than choosing a model for each application
• Optimize for cost, quality, or both, letting you balance performance and budget
• Integrate seamlessly with existing Gemini APIs and SDKs
• Track usage and identify potential for cost savings
• Efficiently handle text-based tasks without a need for manual endpoint selection

Supported models

• Gemini 2.0 Flash (GA)
• Gemini 2.5 Pro (preview, 03-25)

Language support

Model Optimizer supports all languages that are also supported by the Gemini models. (See Gemini Language support)

Modality

Model Optimizer supports text use cases, including:

• Coding, including function calling and code execution
• Summarization
• Single and multi-turn chat
• Question and answering

For limitations and how to handle them, see Handling unsupported features.

Getting started

To get started with Model Optimizer, see our quickstart Colab notebook.

Using Vertex AI Model Optimizer

pip install --upgrade google-genai

# Replace the `GOOGLE_CLOUD_PROJECT` and `GOOGLE_CLOUD_LOCATION` values
# with appropriate values for your project.
export GOOGLE_CLOUD_PROJECT=GOOGLE_CLOUD_PROJECT
export GOOGLE_CLOUD_LOCATION=global
export GOOGLE_GENAI_USE_VERTEXAI=True

#     from google import genai
#     from google.genai.types import (
#         FeatureSelectionPreference,
#         GenerateContentConfig,
#         HttpOptions,
#         ModelSelectionConfig
#     )
#
#     client = genai.Client(http_options=HttpOptions(api_version="v1beta1"))
#     response = client.models.generate_content(
#         model="model-optimizer-exp-04-09",
#         contents="How does AI work?",
#         config=GenerateContentConfig(
#             model_selection_config=ModelSelectionConfig(
#                 feature_selection_preference=FeatureSelectionPreference.BALANCED  # Options: PRIORITIZE_QUALITY, BALANCED, PRIORITIZE_COST
#             ),
#         ),
#     )
#     print(response.text)
#     # Example response:
#     # Okay, let's break down how AI works. It's a broad field, so I'll focus on the ...
#     #
#     # Here's a simplified overview:
#     # ...

Handling unsupported features

Model Optimizer only supports text input and output. However, the request could include different modalities or tools that aren't supported. The following sections cover how Model Optimizer handles these unsupported features.

Multimodal requests

Requests that include prompts with multimodal data, such as video, images or audio, will throw an INVALID_ARGUMENT error.

Unsupported tools

Model Optimizer only supports function declaration for requests. If a request contains other tool types including google_maps, google_search, enterprise_web_search, retrieval, or browse, an INVALID_ARGUMENT error is thrown.

Send feedback

To send feedback about your experience with Model Optimizer, fill out our feedback survey.

If you have questions, technical issues, or feedback about Model Optimizer, contact model-optimizer-support@google.com.

Customer discussion group

To connect directly with the development team, you can join the Vertex AI Model Optimizer Listening Group, where you can learn about the product and help us understand how to make the features work better for you. The group's activities include:

• Virtual workshops to learn more about the features
• Feedback surveys to share your needs and priorities
• 1:1 sessions with Google Cloud employees as we explore new features

Activities are offered about once every 6-8 weeks. You can take part in as many or as few as you'd like, or you can opt out entirely at any time. To join the group, complete the Vertex AI Model Optimizer discussion group sign up form.