GoKawiilGoogle adds agentic video understanding to Gemini 3.7, 3.6 and 3.5 Flash models
Google has upgraded Gemini's video analysis with a new 'agentic' approach that lets the AI selectively choose which frames, audio, or transcript segments to review instead of processing every frame. The company says this cuts token usage by up to 88% while improving accuracy by up to 7%, and enables tracking of object counts, movement, and sub-second events across multi-hour videos. The feature currently works through the Gemini API in AI Studio and the Enterprise Agent Platform, with plans to reach the Gemini app and YouTube's 'Ask YouTube' tool soon.
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Video analysis has historically been expensive and slow for AI models because processing every frame consumes massive amounts of compute and tokens. By letting Gemini intelligently decide what parts of a video matter, Google is making long-form video comprehension practical and affordable at scale, which could benefit creators, enterprises, and eventually everyday users searching or querying video content on YouTube.
- Agentic video understanding cuts Gemini's token usage by up to 88% versus older frame-by-frame processing.
- New capability enables object counting, movement tracking, and sub-second accuracy in long videos.
- Feature is live via Gemini API and Enterprise Platform now, with app and YouTube integration coming soon.
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Published there as: “Gemini now analyzes your videos more accurately, and at a lower cost”
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