gemini-2.5-flash-tts

Neural Network

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gemini-2.5-flash-tts

Specifications

Input
text, images, documents
Output
text
Context size
65 536 tokens
Max answer length
32 000 tokens
Reasoning effort
low, medium, high
Capabilities
reasoning, function calling
160 $

Prompt cost

(per 1M tokens)

160 $

Answer cost

(per 1M tokens)

0,16 $

Image prompt

(per 1K tokens)

*Prices are shown for API usage via ECO providers.
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Code example and API for gemini-2.5-flash-ttsWe offer full access to the OpenAI API through our service. All our endpoints fully comply with OpenAI endpoints and can be used both with plugins and when developing your own software through the SDK.Create API key
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How it works gemini-2.5-flash-tts?

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Frequently asked questions about gemini-2.5-flash-tts

Can I use gemini-2.5-flash-tts results for commercial purposes?

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.

What can gemini-2.5-flash-tts do and what tasks is it suitable for?

According to our data, the model accepts text, images, and documents, can reason before answering, and call functions. It is suitable for parsing files and screenshots, preparing and editing texts, including lines for voiceovers, as well as for scenarios where the response needs to be returned as structured JSON.

How much text can gemini-2.5-flash-tts write in a single response?

The limit for a single response is 32,000 tokens, which is dozens of pages. The total context window is 65,536 tokens, and it includes everything: your request, attached documents, and the response itself. If the material is large, break the task into parts to keep some context buffer.

Can gemini-2.5-flash-tts reason before answering?

Yes, reasoning before answering is confirmed by our data. The model can break down a task into steps and only then provide a result — this is noticeable when parsing documents, comparing options, and in tasks where the sequence of actions is important, rather than the first formulation that comes to mind.

Does gemini-2.5-flash-tts support function calling and JSON output?

Yes, function calling and structured JSON output are supported. The model can be connected to your tools to receive responses in a specified schema. In BotHub, it is available via a unified OpenAI-compatible API, so switching to another model does not require rewriting the integration.

Can I upload images, audio, or video to gemini-2.5-flash-tts?

According to our data, in addition to text, images and documents are accepted as input: you can send a screenshot, diagram, scan, or file and ask to parse the content. Support for audio and video is not noted in our data, so such formats should be tested with your specific task.

How well does gemini-2.5-flash-tts understand Russian?

Our data does not track prompt and response languages, so we cannot make exact promises here — it is easier to test the model with your typical request. The BotHub service itself works in Russian, is available from Russia without a VPN or foreign card, and payments are processed with Russian cards.

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