What is actually a “complex problem” for LLMs?

I keep seeing advice like “use this model for the easy stuff and that one for complex problems.” But it makes me wonder — what really counts as a complex problem for an LLM?

For us, complex usually means lots of steps, deep reasoning, or tricky knowledge. But for AI, the definition might be different. Some things that feel easy for us can be surprisingly hard for models, while things that seem tough for us (like scanning huge datasets quickly) might be trivial for them.

So, I’m curious — how do you think about this? What do you consider a “complex problem” when working with LLMs?