Listen: How Google Decides When to Use Gemini Grounding for User Queries
Google uses dynamic retrieval to decide when Gemini models should use grounding. A prediction score and configurable threshold determine if a query needs search data.
Transcript
When you ask Google's Gemini model a question, it wants to give you the most accurate and up-to-date answer possible. It does this through a process called grounding, which connects the model's responses to real-time information from Google Search.
But searching the web for every single query isn't practical. It adds lag time and increases costs, especially for simple questions that don't need fresh data. To solve this, Google uses a system called dynamic retrieval.
Before answering, the system evaluates your query and assigns it a prediction score between zero and one. A higher score means the query is highly likely to benefit from a live search. Developers can set a threshold, which defaults to zero point three. If the query's score meets or exceeds that threshold, the system triggers Google Search to ground the response. If the score is lower, Gemini simply relies on its own pre-trained knowledge.
This smart, selective approach keeps costs down and response times fast, while ensuring you get the most accurate, grounded answers when they matter most.