Unverified50% confidenceTradeoffExact time
The cost of ReAct is that each loop adds one model call, with latency and token consumption growing linearly with the number of steps, so real systems typically set a maximum number of iterations and early-termination conditions.
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50%
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Long-term
Relevance
10/17/2026
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Related Claims
UnverifiedIn actual engineering, a maximum number of iterations (Max Iterations) is typically set for the ReAct loop to prevent the Agent from entering an infinite loop or consuming excessive resources79% similarUnverifiedReAct complex tasks may consume multiple rounds of LLM calls, impacting both latency and cost, making them a key factor to weigh in real-world deployments.74% similarUnverified典型的Agent框架如ReAct、AutoGPT、LangGraph采用感知-推理-行动的迭代模式，上下文随轮次累积导致后期每轮Token消耗呈线性甚至指数增长71% similarUnverifiedEach step of the iterative loop consumes API call quota for the large model, and costs can accumulate quickly for complex tasks.71% similarUnverifiedIn loop scenarios, each iteration requires feeding the entire conversation history back into the model, causing per-iteration token consumption to increase incrementally due to context accumulation, resulting in a cost curve steeper than linear.71% similar
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