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标题: "Optimize Cheap, Deploy Strong: Cost-Aware Cross-Tier Transfer for Evolutionary Optimization"
原文链接: "https://arxiv.org/abs/2608.10694"
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---

## Computer Science > Machine Learning

## Title:Optimize Cheap, Deploy Strong: Cost-Aware Cross-Tier Transfer for Evolutionary Optimization

Authors:[Tal Oved](https://arxiv.org/search/cs?searchtype=author&query=Oved,+T), [Roi Pony](https://arxiv.org/search/cs?searchtype=author&query=Pony,+R), [Oshri Naparstek](https://arxiv.org/search/cs?searchtype=author&query=Naparstek,+O), [Udi barzelay](https://arxiv.org/search/cs?searchtype=author&query=barzelay,+U)

[View PDF](https://arxiv.org/pdf/2608.10694) [HTML (experimental)](https://arxiv.org/html/2608.10694v1)

> Abstract:Evolutionary optimization of LLM prompts and agentic programs (e.g., GEPA) is dominated by fitness evaluation: scoring each candidate runs an answering LLM over a validation set, so the evaluator's price tier dictates total search cost. We restructure that search by decoupling the three roles an LLM plays, running the high-volume answering role on the cheapest tier, reserving a strong model for the rare reflection/variation operator, then exploiting upward cross-tier transfer to deploy the cheaply evolved prompt on a stronger target. We contribute a cost-controlled characterization of when cheap-tier search substitutes for target-tier search, and where it fails. Across four tasks (HotpotQA, IFBench, LiveBench-Math, HoVer) and eleven models in four model families, the resulting prompt matches or exceeds same-tier optimization while placing over 96% of search tokens on the cheapest tier, at 5.6-14x lower search cost, rising to 25-54x where reasoning tiers emit long chains of thought on every fitness call.

| Subjects: | Machine Learning (cs.LG); Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Neural and Evolutionary Computing (cs.NE) |
| --- | --- |
| Cite as: | [arXiv:2608.10694](https://arxiv.org/abs/2608.10694) \[cs.LG\] |
|  | (or [arXiv:2608.10694v1](https://arxiv.org/abs/2608.10694v1) \[cs.LG\] for this version) |
|  | [https://doi.org/10.48550/arXiv.2608.10694](https://doi.org/10.48550/arXiv.2608.10694) |

## Submission history

From: Tal Oved \[[view email](https://arxiv.org/show-email/3a9e8b3f/2608.10694)\]  
**\[v1\]** Tue, 11 Aug 2026 09:17:22 UTC (558 KB)

[Which authors of this paper are endorsers?](https://arxiv.org/auth/show-endorsers/2608.10694) | Disable MathJax ([What is MathJax?](https://info.arxiv.org/help/mathjax.html))
