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LLM Benchmarks & Leaderboards

Each benchmark below ranks large language models on a specific task — and pairs every score with the model's cost per million tokens, so you can see which model is the best value, not just the highest score.

Decision-model benchmarks

Decision models answer typed questions with calibrated probabilities instead of generating text. These boards rank them on accuracy, with calibration (ECE) and latency alongside. See all decision models.

System One benchmark

Decision models, not chat models: TypeSafe's Jev and every open alternative (LAYA, Von, GLiNER2, GLiClass) measured on 2,123 judgments through one harness — accuracy, calibration, latency.

View the System One leaderboard →

Looking for the underlying datasets? Browse our benchmark datasets (MMLU, GPQA, HumanEval and more).