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Gemini Exp 1114

Google (Gemini)

At a glance

Price per 1M tokens (input)
free
Price per 1M tokens (output)
free
Context
1,048,576 tokens
Free access
yes (see below)

Refreshed daily; data verified August 15, 2026. Published August 12, 2026.

The Gemini Exp model is designed for businesses and developers who need to analyze and understand visual data, as well as integrate with external tools and services. This model excels at tasks such as image classification, object detection, and image segmentation, making it a valuable asset for applications like content moderation, product categorization, and medical imaging. What sets the vendor's approach apart is the emphasis on tool calling, which allows the model to leverage the capabilities of external functions and services, enabling more complex and nuanced workflows. By combining image understanding with tool calling, the Gemini Exp model provides a powerful foundation for building sophisticated AI-powered systems. The vendor's approach focuses on providing a flexible and adaptable framework that can be tailored to meet the specific needs of various industries and use cases.

Specifications & pricing

Input (per 1M tokens)free
Output (per 1M tokens)free
Context window1,048,576 tokens
Max output8,192 tokens
Capabilitiesimages, tool calling

LiteLLM community dataset (MIT), verified August 15, 2026. Official Google (Gemini) pricing.

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Frequently asked questions

What is the Gemini Exp model good for+

The Gemini Exp model is well-suited for tasks that involve analyzing and understanding visual data, such as images and videos, as well as integrating with external tools and services to enable more complex workflows

How do I get started with the Gemini Exp model+

To get started with the Gemini Exp model, you will need to familiarize yourself with the model's capabilities and limitations, as well as the vendor's documentation and support resources, which provide guidance on integration, deployment, and optimization

How does the Gemini Exp model differ from other models in the line+

The Gemini Exp model differs from other models in the line in its emphasis on tool calling, which allows it to leverage the capabilities of external functions and services, enabling more complex and nuanced workflows than other models that focus solely on image understanding

What are the limitations of the Gemini Exp model+

The limitations of the Gemini Exp model include its reliance on high-quality training data, as well as potential biases and errors that can occur when integrating with external tools and services, which must be carefully evaluated and mitigated to ensure optimal performance

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