Claude 3 Opus

Crowdsourced pairwise human preference rankings of LLM responses. Higher Elo means more frequently preferred by users.

American Invitational Mathematics Examination 2024 problems. Three-digit integer answers; very hard for non-reasoning models.

AIME-style competition problems written specifically for the OTIS mock contest, then run as an evaluation by Epoch AI. Closer in spirit to the public AIME but with novel problems unlikely to appear in training data.

164 hand-written Python programming problems scored by passing unit tests. Saturated for frontier models.

Real GitHub issues solved end-to-end. Verified subset is a 500-task human-validated slice of SWE-bench.

Massive Multi-discipline Multimodal Understanding; college-exam level questions with images across 30+ subjects.

Math reasoning over visual contexts (charts, figures, geometry).

Long-context retrieval and reasoning suite. We report the 128k token effective-context score.

Median output speed in tokens per second over the last 14 days on the model maker's own API, measured nightly with a fixed ~800-token prompt and ~250-token answer. Models not yet probed fall back to a dated manual figure. Higher is faster.

Median time from request to first streamed token in milliseconds over the last 14 days on the model maker's own API, using the same nightly probe prompt. Lower is snappier; reasoning models are penalised here because they think before talking.

A human-validated factuality benchmark of short factual questions whose answers can be checked against a single ground truth. Penalises hallucinations by scoring confidently-wrong answers below abstentions.

Saturation-resistant composite capability score stitched together from ~40 underlying benchmarks using Item Response Theory. Each benchmark is weighted by its fitted difficulty and discriminative slope, so doing well on hard, contamination-resistant evals (FrontierMath, ARC-AGI 2, Humanity's Last Exam) moves the score and saturated benchmarks contribute almost nothing. Imported per-model from Epoch AI's published index; we anchor it to the same min-max scale we use for every other benchmark so it's directly weightable in scenarios.