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Gemini Robotics Er 1.5 Preview

Google (Gemini)

At a glance

Price per 1M tokens (input)
$0.30
Price per 1M tokens (output)
$2.50
Context
1,048,576 tokens
Free access
yes (see below)

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

The Gemini Robotics Er model is designed for businesses and organizations that require advanced image understanding and step-by-step reasoning capabilities. This model suits tasks such as image analysis, object detection, and automated decision-making. What distinguishes the vendor's approach is the integration of tool calling, which allows the model to invoke specific functions or tools to perform complex tasks. This enables the model to go beyond simple image recognition and provide more nuanced and accurate results. The vendor's approach also emphasizes the importance of explainability and transparency in the model's decision-making process.

Specifications & pricing

Input (per 1M tokens)$0.30
Output (per 1M tokens)$2.50
Cache read (per 1M tokens)free
Context window1,048,576 tokens
Max output65,535 tokens
Capabilitiesimages, tool calling, reasoning

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

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Frequently asked questions

What is the Gemini Robotics Er model good for+

The Gemini Robotics Er model is good for tasks that require advanced image understanding and step-by-step reasoning, such as image analysis and object detection

How do I get started with the Gemini Robotics Er model+

To get started with the Gemini Robotics Er model, you will need to familiarize yourself with the model's capabilities and limitations, and then integrate it into your existing workflow or application, using the vendor's provided APIs and tools, including tool calling, which allows the model to invoke specific functions or tools

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

The Gemini Robotics Er model differs from other models in the line in its emphasis on image understanding and step-by-step reasoning, as well as its ability to perform tool calling, which sets it apart from more general-purpose models

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