REDDIT · REDDIT// 29d agoBENCHMARK RESULT

LEVI beats GEPA, OpenEvolve on budget

LEVI is a new LLM-guided evolutionary optimization framework that emphasizes search-harness design over frontier-model dependence, using cheaper models for most mutations and stronger models only for paradigm shifts. Based on its published ADRS and circle-packing results, it reports better or tied performance against GEPA/OpenEvolve baselines at significantly lower cost and has released code on GitHub.

// ANALYSIS

The interesting claim here is not just higher scores, but that architecture and diversity strategy can outperform brute-force model spend in evolutionary coding loops.

–LEVI’s stratified model allocation pushes most mutation traffic to cheaper Qwen-class models, reserving expensive calls for rare high-creativity steps.
–Its fingerprint-based CVT-MAP-Elites combines structural and performance diversity, which helps keep search breadth without collapsing too early.
–Controlled comparisons on the same model and evaluation budget suggest the gain is in search mechanics, not simply model quality.
–If these results replicate broadly, LEVI could lower the cost floor for ADRS-style optimization and make this workflow practical for smaller teams.

// TAGS

levillmbenchmarkresearchopen-source

DISCOVERED

29d ago

2026-03-14

PUBLISHED

30d ago

2026-03-12

RELEVANCE

9/ 10

AUTHOR

Longjumping-Music638