gemini-omni-flash-preview
Neural Network
Specifications
- Input
- text, images, documents
- Output
- text
- Context size
- 131 072 tokens
- Max answer length
- 32 000 tokens
- Reasoning effort
- low, medium, high
- Capabilities
- reasoning, Batch API
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
Image prompt
(per 1K tokens)
How it works gemini-omni-flash-preview?
Frequently asked questions about gemini-omni-flash-preview
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.
The google-gemini model works with text, images, and documents: it answers questions, analyzes and fixes code, helps with reasoning and STEM tasks, and extracts meaning from uploaded files. It is suitable for assistants, document analysis, and work scenarios requiring a context of up to 65,536 tokens.
Up to 32,000 tokens in a single response — that's dozens of pages of text. Enough for a long document analysis, a detailed article, or a large block of code in its entirety. If there is more material, break the task into parts and assemble the result with sequential requests in one dialogue.
Yes, the model's reasoning mode is confirmed: before answering, it breaks down the task step-by-step rather than providing the first solution that comes to mind. The difference is noticeable in math, logic, code debugging, and multi-step questions where the chain of reasoning is important, not just speed.
In our data, function calling and structured JSON output are not noted, but that does not mean they are absent. If you are building an agent or integration, test the schema with your scenario: BotHub has a unified OpenAI-compatible API, and if necessary, you can switch to another model without rewriting code.
Images and documents — yes: send a screenshot, diagram, or file and ask to analyze the content. Audio and video input are not noted in our data, so count on images and documents, and for audio, choose a specialized model from the catalog.
Language characteristics are not specified in our data, so we will not promise exact formulations. Gemini is a multilingual family of models, and such models usually handle Russian queries without issues. It is more reliable to test it with your own task: BotHub offers access without VPN or foreign cards, with payment via Russian cards.