Google’s Gemini 2.5 Flash is the company’s first hybrid reasoning model, merging the speed and cost‑efficiency of 2.0 Flash with adjustable thinking budgets so developers can balance quality, cost, and latency.
The company that provides the model
The number of tokens you can send in a prompt
The maximum number of tokens a model can generate in one request
The cost of prompt tokens sent to the model
The cost of output tokens generated by the model
When the model's knowledge ends
When the model was launched
Capability for the model to use external tools
Ability to process and analyze visual inputs, like images
Support for multiple languages
Whether the model supports fine-tuning on custom datasets
Gemini 2.5 Flash is Google’s first hybrid reasoning model, combining the speed and cost-efficiency of the 2.0 Flash model with adjustable thinking budgets. This allows developers to balance quality, cost, and latency in their applications.
Gemini 2.5 Flash has a cost structure of $0.15 per million input tokens and $0.60 per million output tokens, though it is free during the experimental stage.
The input token cost for Gemini 2.5 Flash is $0.15 per million input tokens.
The output token cost for Gemini 2.5 Flash is $0.60 per million output tokens.
Gemini 2.5 Flash supports a context window of up to 1,048,576 tokens, which allows it to handle large and complex inputs effectively.
Gemini 2.5 Flash can generate up to 65,536 tokens in a single output.
Gemini 2.5 Flash was released on April 17, 2025.
The knowledge cut-off date for Gemini 2.5 Flash is January 1, 2025.
Yes, Gemini 2.5 Flash supports tool calling, allowing it to use external tools as part of its operations.
Yes, Gemini 2.5 Flash supports vision capabilities, allowing it to process and analyze visual inputs like images.
Yes, Gemini 2.5 Flash supports multiple languages, making it suitable for global applications.
No, Gemini 2.5 Flash does not support fine-tuning.
You can find the official documentation for Gemini 2.5 Flash here:
Gemini 2.5 Flash Documentation
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