You can use generated results for commercial purposes. You own all rights to the content you create. The only restriction: make sure your prompt does not include copyrighted third-party material. You are responsible for respecting the rights to any input data.

This is a Google text model with reasoning support: it analyzes long documents, answers questions about images, writes and edits code, and helps with STEM tasks and analytics. It is suitable for chats, assistants, and processing large volumes of text where response speed is important.

In a single response, the model outputs up to 32,000 tokens — enough for a lengthy article, detailed documentation, or a large code module. The total context window is 65,536 tokens, so keep in mind that the request and response share it.

Yes, the reasoning mode is confirmed: before the final answer, the model runs an internal chain of steps. This helps with math, logic, code analysis, and multi-step tasks where not only the result but also the correct path to it is important.

Yes. The model supports function calling and structured JSON output, making it easy to integrate into agents and pipelines: it selects the necessary tool itself and returns the answer in the specified schema. In BotHub, this is available via a unified OpenAI-compatible API.

According to our data, images and documents are accepted as input: you can send a screenshot, photo, diagram, or a file with a table and ask to analyze the content. Audio and video support is not specifically noted, so such scenarios should be tested with your specific task.

Our data does not specifically describe the language of requests and responses, so we make no exact promises. The Gemini family generally works with many languages, so it is easiest to test with your own task: ask a couple of typical questions and compare the answer with another model in the same BotHub window.