Chain-of-Thought vs. Tree-of-Thought: Which Reasoning Pattern Wins in Complex Prompts?

For deep reasoning or multi-step problem solving, many of us rely on Chain-of-Thought (CoT) — the classic linear reasoning style where the model explains step-by-step thinking.

But lately, I’ve seen more people experimenting with Tree-of-Thought (ToT) prompting — where the model explores multiple reasoning paths before deciding which one leads to the best answer.

Some claim Tree-of-Thought unlocks better exploration, error recovery, and creative reasoning for tasks like:

strategy generation

complex analysis

game theory / planning

multi-objective decision making

In my own testing, ToT can outperform CoT — but only if the model supports self-evaluation or reflection steps. Otherwise, it sometimes spirals into overthinking.

So I’m curious about the community’s experience:
👉 Have you tested CoT vs. ToT on real-world prompts (analysis, writing, coding, etc.)?
👉 Does ToT actually yield better results, or is it just slower with diminishing returns?

Would love to see shared experiments, examples, or even your favorite ToT-style prompts.