SpecEvo reduces API cost by up to 80% and improves discovery efficiency
Researchers present SpecEvo, a multi‑LLM framework that orchestrates lightweight and frontier models for scientific discovery. Lightweight models act as parallel Speculators that generate and refine candidate programs, while an Advisor consolidates successes, failures, and saturated directions into ongoing guidance. At occasional checkpoints, a frontier‑model Navigator reviews the population and…
Key points
- SpecEvo coordinates lightweight Speculators, an Advisor, and a frontier‑model Navigator for scientific search
- On 176 tasks across four domains, it reduces API cost by up to 80% and boosts evaluation efficiency up to 1.5x
- Performance exceeds the strongest CO‑Bench baseline by 3.8% while matching frontier‑model baselines
Across 176 tasks in four scientific and algorithmic discovery domains, SpecEvo matches or outperforms frontier‑model baselines, cuts API cost by up to 80%, achieves up to 1.5x greater evaluation efficiency on equation discovery, and improves over the strongest CO‑Bench baseline by 3.8%. The authors argue that coordinating models by trajectory‑conditioned roles can make large‑scale discovery more cost‑effective.
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