A lot of people still have a shallow understanding of how LLMs work. Each version of a model has different qualities than the last, each model is better or worse at some things than others, and each responds differently to different prompts, styles. Some smaller models perform better than larger ones. Sometimes you should use a system prompt, sometimes you shouldn't. Tuning settings for the model inference (temperature, top_p, penalties, etc) significantly influence the outcome. (https://www.promptingguide.ai/introduction/settings, https://platform.openai.com/docs/guides/optimizing-llm-accur...)

Most "big name" models' interfaces don't let you change settings, or not easily. Power users learn to use different interfaces and look up guides to tweak models to get better results. You don't have to just shrug your shoulders and switch models.

Gemini has a great model, but it's a bad product. I feel much happier using ChatGPT because Gemini just seems so barebones and unpolished. It has this feeling of a tech demo.

Scientific research and proof-reading. Gemini is the laziest LLM I've used. Frequently he will lie that he searched for something and just make stuff up, basically never happens to me when I'm using gpt5.2.

In my experience with Gemini, I find it incapable of not hallucinating.