The Gemini 2.5 model is truly impressive, especially with its multimodal capability. Its ability to understand audio and video content is amazing—truly groundbreaking.

I spent some time experimenting with Gemini 2.5, and its reasoning abilities blew me away. Here are few standout use cases that showcase its potential:

1. Counting Occurrences in a Video

In one experiment, I tested Gemini 2.5 with a video of an assassination attempt on then-candidate Donald Trump. Could the model accurately count the number of shots fired? This task might sound trivial, but earlier AI models often struggled with simple counting tasks (like identifying the number of "R"s in the word "strawberry").

Gemini 2.5 nailed it! It correctly identified each sound, outputted the timestamps where they appeared, and counted eight shots, providing both visual and audio analysis to back up its answer. This demonstrates not only its ability to process multimodal inputs but also its capacity for precise reasoning—a major leap forward for AI systems.

2. Identifying Background Music and Movie Name

Have you ever heard a song playing in the background of a video and wished you could identify it? Gemini 2.5 can do just that! Acting like an advanced version of Shazam, it analyzes audio tracks embedded in videos and identifies background music. I am also not a big fan of people posting shorts without specifying the movie name. Gemini 2.5 solves that problem for you - no more searching for movie name!

3. OCR Text Recognition

Gemini 2.5 excels at Optical Character Recognition (OCR), making it capable of extracting text from images or videos with precision. I asked the model to output one of Khan Academy's handwritten visuals into a nice table format - and the text was precisely copied from video into a neat little table!

4. Listen to Foreign News Media

The model can translate text from one language to another and give a good translation. I tested the recent official statement from Thai officials about an earthquake in Bangkok, and the latest news from a Marathi news channel. The model was correctly able to translate and output the news synopsis in the language of your choice.

5. Cricket Fans?

Sports fans and analysts alike will appreciate this use case! I tested Gemini 2.5 on an ICC T20 World Cup cricket match video to see how well it could analyze gameplay data. The results were incredible: the model accurately calculated scores, identified the number of fours and sixes, and even pinpointed key moments—all while providing timestamps for each event.

7. Webinar - Generate Slides from Video

Now this blew my mind - video webinars are generated by slide decks and a person talking about the slides. Can we reverse the process? Given a video, can we ask AI to output the slide deck? Google Gemini 2.5 outputted 41 slides for a Stanford webinar!

Bonus: Humor Test

Finally, I put Gemini 2.5 through a humor test using a PG-13 joke from one of my favorite YouTube channels, Mike and Joelle. I wanted to see if the model could understand adult humor and infer punchlines.

At first, the model hesitated to spell out the punchline (perhaps trying to stay appropriate?), but eventually, it got there—and yes, it understood the joke perfectly!

https://videotobe.com/blog/googles-gemini-25