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协调税与异构红利:多智能体 LLM 流水线的盈亏平衡条件

The Coordination Tax and the Heterogeneity Dividend: Break-Even Conditions for Multi-Agent LLM Pipelines

Andreas Zettl · Diego Gosmar

中文摘要

基于 Open Floor Protocol (OFP) 或 A2A 等互操作协议构建的多智能体 LLM 流水线,通常以能力为由获得支持,其运行时成本被视为规模未知的开销。将此类流水线与单次模型调用比较并不充分,因为流水线可为每个角色分配不同模型。给出闭式模型,将协调税(分解开销加每次交接协议成本)与把工作路由到更便宜模型带来的异构红利对比,给出盈亏平衡阈值与可行性界 α < 1/r,并以 OFP 为被测协议,在 135 个 HumanEval 和 ClassEval 任务上测量各项,共 2430 次运行、六种架构、Claude Opus 5.5 与 Haiku 5.5。协议每次交接增加 7.2 ms,占流水线墙钟时间 0.11%。分解在这些任务上不划算:planner-coder-reviewer 流水线成本是单次强调用的 3.22 倍,耗时 3.24 倍,且未多解任务。将 planner 与 reviewer 换成便宜模型后,流水线成本降至 0.39 倍,但 pass@1 变化 -6.7 个百分点,仍比单次调用更贵、更慢、更不准;盈亏平衡预测偏差 -19%,因便宜角色抬高了 token 量。节省在于按任务选模型:在两个单次调用间做 oracle 选择,以强调用每解一题成本的一半,解决 94.3% 的运行。

关键要点

  1. 01多智能体流水线成本常被当作未知开销,缺少与单次调用的定量比较。
  2. 02提出闭式模型,用协调税与异构红利给出盈亏平衡阈值和可行性界 α < 1/r。
  3. 03在 135 个任务 2430 次运行中,OFP 每次交接仅增 7.2 ms,占墙钟 0.11%。
  4. 04planner-coder-reviewer 流水线成本 3.22 倍、耗时 3.24 倍,且未多解任务。
  5. 05按任务在两次单次调用间 oracle 选择,以一半成本解决 94.3% 运行。

解读

尚无解读。

原始英文摘要

arXiv:2610.37700v1 Announce Type: cross Abstract: Multi-agent LLM pipelines built on interoperability protocols such as the Open Floor Protocol (OFP) or A2A are usually justified on capability grounds, with their runtime cost treated as an overhead of unknown size. Comparing such a pipeline with one model call is underspecified, because a pipeline can give each role a different model. We give a closed-form model that sets the coordination tax (decomposition overhead plus per-handoff protocol cost) against the heterogeneity dividend from routing work to a cheaper model, with a break-even threshold and a feasibility bound, $\alpha < 1/r$, and measure every term, with OFP as the protocol under test, on 135 HumanEval and ClassEval tasks in 2430 runs of six architectures with Claude Opus 5.5 and Haiku 5.5. The protocol adds 7.2 ms per handoff, 0.11% of pipeline wall time. Decomposition does not pay on these tasks: a planner-coder-reviewer pipeline costs 3.22x as much as a single strong call, takes 3.24x as long, and solves no more tasks. Moving planner and reviewer to the cheap model cuts the pipeline's cost to 0.39x but changes pass@1 by -6.7 points, leaving it dearer, slower and less accurate than the single call, and the break-even forecast misses by -19% because the cheap roles inflate token volume. The saving lies in choosing a model per task instead: an oracle choice between the two single calls solves 94.3% of runs at half the strong call's cost per solved task.

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