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ZDNET's key takeaways
Different AI models win at images, coding, and research.
App integrations often add costly AI subscription layers.
Obsessing over model version matters less than workflow.
The pace of change in the burgeoning generative AI world is blisteringly fast. It's often hard to keep up with everything, even if it's your full-time job. Readers tell me that one area they find particularly confusing is the wide array of poorly-named AI models. What in the heck is the difference between GPT-5.1, Opus 4.5, Gemini 3, etc.? And why would you use one over the other?
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To be honest, trying to fully understand the detailed differences between each of the AI models will send almost anyone screaming into the woods. But it's fairly easy, especially with examples, to understand which models to choose for different tasks. That's what we're going to do in this article.
Keep in mind that apps and AI models are different beasts. The model is the underlying AI engine that does the intelligence processing. The application is the tool you use. Here's a diagram, created in Google's Nano Banana Pro, that gets it mostly right.
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