INDEPENDENT AI MODEL BENCHMARK

QBench Index 1.6

A source-audited view of model capability. Compare exact effort variants, inspect benchmark evidence and explore the trade-offs between capability, coverage and price.

SCORING FRAMEWORK
08 capability familiesEqual-weight observed family means
Exact reported effort variants
Missing scores are never imputed

QBench Index 1.6 leaderboard

How QBench Index 1.6 works
Each benchmark keeps its reported 0–100 accuracy or task-success percentage. Results are averaged inside eight capability families, then the observed family means are averaged equally. Missing families are left out, not imputed and not pulled toward 50. Model effort variants are separate entries; unreported effort is never guessed.
Rank: at least 3 eligible evaluations across 3+ capability families · Evidence: full (all 8 families), broad (4–7), or limited (3) · Insufficient evidence: retained in Models, without an Index score.
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