# Tree of Thoughts

> Tree of Thoughts is a prompting method that explores multiple reasoning branches as a search tree, evaluating and backtracking among them.

**Tree of Thoughts is a prompting and search method that generalizes [chain-of-thought](/glossary/chain-of-thought) into a branching tree: the model generates multiple candidate reasoning steps, evaluates them, and explores or backtracks among branches to reach a solution.**

Where chain-of-thought commits to one linear sequence, Tree of Thoughts treats reasoning as a search problem. At each step it proposes several possible "thoughts," scores how promising each is, and expands the best ones — depth-first or breadth-first — discarding dead ends. Because it can abandon a bad path and try another, it outperforms linear prompting on tasks that need lookahead and exploration, like puzzles and multi-step planning where the first idea is frequently wrong.

The cost is the catch. Exploring a tree means many more model calls and far more tokens than a single pass, which is a deliberate spend of [test-time compute](/glossary/test-time-compute) — trading inference budget for accuracy. That tradeoff also overlaps with what a [reasoning model](/glossary/reasoning-model) does internally, so before orchestrating an explicit tree, it's worth checking whether a reasoning model already gives you enough exploration for far less plumbing.

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_Source: https://agentscamp.com/glossary/tree-of-thoughts — Term on AgentsCamp._