Gemini, ChatGPT and Claude Analyze Video: Which One Wins the Test

The three biggest AI models, Google's Gemini, OpenAI's ChatGPT and Anthropic's Claude, can all analyze video. But which one does it best? Testing on YouTube clips and local files produced a clear leader.

How the test worked

The idea was simple: give all three models the same videos and see which one understands the content best. The author used a varied mix of video content, from popular YouTube clips to his own recordings stored on disk, shot under different lighting conditions and at different quality levels.

Each model got the same questions about each video: what is happening on screen, who is doing what, which details are visible, and what the scene means. The prompts went beyond "describe the video" to specific questions such as "How many people are in the frame?", "What color is their clothing?" and "What is the dialogue about?"

The goal was not to judge how polished the interface looks, but to test real understanding of video content. How does a model handle text in a video? Can it grasp context rather than just count objects?

Results: there is a clear leader

The results were telling. One model clearly outperforms the others in accuracy, analysis speed and contextual understanding. It didn't just list what it saw; it actually understood what was going on and caught important details that the others missed or misinterpreted.

The differences show up in every category:

• Processes video faster
• Recognizes on-screen text more accurately
• Understands complex scene context better
• Invents details that aren't in the video less often

Where the models stumble

There is a caveat, though: all three models are far from perfect at video analysis. Even the test leader can make mistakes with fast-moving objects, blurry footage or specialized content such as technical diagrams, documents and low-quality video.

Text in video remains a hard problem for all three. They often confuse letters, skip words and misread text. Errors are especially common with small text, unusual camera angles and nonstandard fonts.

On top of that, the test was run at a specific point in time (probably early 2024 or 2025), and all three models are constantly improving. New versions may change the results. What's true today may not be true a month from now.

What this means

If you need to analyze video content with AI, your choice of model matters. The test showed that one of the three clearly performs better and will be more useful for real-world workflows, from reviewing video footage to picking out details.

Still, keep in mind that even the best of the three is still a developing technology. Video analysis remains an area prone to errors. Use these results as a guide, but test the models on your own videos before you choose.