
Why I chose Gemini over GPT to power my YouTube title generator — and what I built around it
I built a YouTube title generator. Not because it seemed like a fun side project, but because I genuinely couldn't find one that worked for my own channel. I was running an automation channel and every tool I tried failed in the same way — they generated titles for the wrong creator. VidIQ was handing me MrBeast-style broad clickbait. ChatGPT output that was obviously ChatGPT. Neither understood niche. Neither understood my channel. So I built TitleGen. Here's what I actually decided to build and why. Why Gemini, not GPT. This was the first real decision. Most AI tools default to OpenAI. I went with Gemini as the primary model for one specific reason — it has a deeper contextual understanding of YouTube as a platform. The way it handles creator-specific language, niche terminology, and video metadata is noticeably better for this use case. GPT sits as a fallback in case Google's API ever goes down. That's its only job. The tool isn't a Gemini wrapper though — the model is just one laye
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