Unverified50% confidenceFactExact time
In AI programming scenarios, the single-request input context for a medium-sized Python project may reach 8,000–30,000 tokens, and multi-step tasks in Agent workflows may trigger 5–20 consecutive model calls
1
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50%
Confidence
Long-term
Relevance
9/11/2026
First Seen
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Related Claims
VerifiedIn multi-agent systems, each Agent call must carry the full context, and multi-turn reasoning continuously accumulates conversation history, meaning a seemingly simple multi-Agent task may consume tens of thousands or even hundreds of thousands of Tokens, whereas an equivalent workflow might only require a single call of a few hundred Tokens.71% similarUnverifiedAgent tasks require multiple model invocations, and a 12B model on a consumer-grade GPU already takes several seconds per inference, causing the time cost of multi-step tasks to accumulate significantly.71% similarUnverifiedCoding Agent采用感知-规划-行动循环（类似ReAct框架），复杂任务可能需要数十次内部迭代，每次任务处理可能需要10到15分钟71% similarUnverifiedEvery interaction an AI agent has with a large model consumes tokens; a single complex task may trigger dozens of model calls, with each call typically incurring a latency of 1–10 seconds.71% similarUnverifiedIn agentic scenarios, large models can be used to generate high-quality task execution trajectories, which are then used to fine-tune models that are 10–100 times smaller in parameter count to perform specific subtasks.70% similar
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