There are a lot of AI models out there, so in this video I break down the main “types” of models and how I actually pick between them for real projects. The easiest mental model (in my opinion) is capability vs size vs speed vs cost—so I use a plane analogy: flagship models are like huge commercial jets (powerful but expensive and slower), light models are like private jets (fast and cheap but less capable), mid-tier models are the Boeing 737 workhorses (what you’ll use for ~80% of tasks), and specialist models are like search-and-rescue helicopters (built for one job). I walk through concrete examples: OpenAI GPT 5.2 as a super well-rounded flagship that can chain actions and do multimodality; Claude Opus 4.6 as an absolute monster for writing + code (but slow/expensive and not great at image generation); Grok 4.1 as a weirdly good “anomaly” that’s fast, cheap, huge context, and high-EQ; and Gemini 3 Pro as a flagship that really shines on multimodality and character-consistent image generation. Then I compare Gemini 3 Flash vs Pro to show why “lite” models can be perfect when you need speed, and I explain why Claude Sonnet 4.5 is my favorite mid-tier model for building apps from scratch. Finally, I cover open source models like Kimi K2.5 (cheap + privacy + control) and specialist research models like Perplexity’s Sonar for citations-heavy answers. The goal is that next time you see a new model name, you can instantly categorize it and not feel overwhelmed.