Why does ReAct carry higher latency and cost than Plan-and-Execute?

ReAct's core loop performs a full reasoning-action-observation cycle before every single step, which means every action in a multi-step task pays for another round of model inference.

• Each cycle consumes additional tokens for the reasoning text generated before the action
• Sequential reasoning and observation steps add latency, since each one depends on the result of the previous action
• Costs become less predictable, since the number of cycles needed to finish a task isn't known upfront

Plan-and-Execute avoids most of this overhead by generating the full plan once and executing it with minimal re-reasoning, at the cost of being less able to adapt if the plan turns out to be wrong partway through.

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