Model Leaderboards

Benched.ai Editorial Team

Model leaderboards rank AI models across standardized benchmarks and publish scores publicly to guide selection.

Common Leaderboards

Name	Focus	Metrics
Hugging Face Open LLM	LLMs	MMLU, ARC, TruthfulQA
LMSYS Chatbot Arena	Chat agents	Elo from pairwise votes
Papers with Code Image	Vision	Top-1 accuracy

Transparency Checklist

Public eval code and dataset hashes.
95 % confidence intervals.
Disclosure of test-time compute.

Design Trade-offs

Public leaderboards drive progress but encourage overfitting.
Private benchmarks may better match enterprise tasks but lack transparency.

Current Trends (2025)

Continuous evaluation pipelines auto-score new commits.
Multi-modal boards aggregate text, vision, audio into single page.
Leaderboards offer paid "certified run" badges for reproducibility.

Implementation Tips

Host raw outputs for community auditing.
Rate-limit submission frequency to avoid spam.
Use Docker images to standardize runtime.