Crowdsourced Pairwise Model Comparison Via Battle Mode

via “batch pairwise evaluation with sampling and tournament modes”

Automatic LLM evaluation — instruction-following, LLM-as-judge, length-controlled, cost-effective.

Unique: Implements three distinct evaluation modes (pairs, head-to-head, sampling) within a unified API, allowing users to choose evaluation strategy based on budget and model count. The sampling mode enables approximate rankings for large model sets without quadratic cost, using statistical sampling rather than exhaustive comparison.

vs others: More flexible than single-mode benchmarks; sampling strategy is more cost-effective than exhaustive pairwise comparison for large model sets