I similarly have a weird affinity for Gemini that I can't really articulate. I used Gemini's free chat and found it great for exploring technical topics (and random one-off general walking-around-questions) and appreciated its speed, tone and accuracy. I spent a month playing with Gemini CLI / Antigravity and found it also an effective coding agent, at least for my workflow (entirely in the loop development and review). I also was really surprised that I could just paste it images of a project I was working on and have it immediately understand what it was looking at -- which I've come to learn is considered a unique strong point for Gemini. I've been playing with GPT5.6 for about a month and it's definitely powerful but I honestly think I'll go back to Gemini. There's something kind of charming about working with an AI that not only is particularly good at web search and information gathering, but also one that doesn't feel like some superhuman overengineering freak when it comes to code.
I like to think of Gemini as a broader generalist that hasn't allocated _most_ of its skillpoints to agentic coding execution :)
Well, Google is probably the only one among frontier model providers in the US that doesn't have a massive financial pressure to deliver business results ASAP (and this focus on agent coding and long-running agentic tasks), so Google is able to focus more on encoding deep scientific, cultural and historical knowledge to its systems. I'd assume DeepMind's focus on the scientific core also played a role in the tone and approach Gemini models take for explanations and Q&As.
I find that GPT models and Claude tend to talk in strong slangs and in-group jargon, but love Gemini's massive general knowledge corpus — reminds me of Richard Feynman from his lectures.