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Model profile

O1 Mini

OpenAIdeveloper
2024-09-12release date
#92 / 267overall rank
11eval lineages

Evidence summary

O1 Mini has an estimated overall rank of #92; its 90% source-sensitivity interval is #18–#199. Its behavior-only rank is #95; company governance moves the combined estimate to #92. Published evidence spans 11 evals and 7 of 7 behavior components. Its strongest relative result is Large-scale Moral Machine experiment on LLMs (human_choice_distance, #1 of 39); its weakest is AIRBench 2024 Safety Scenarios (safety_scenarios, #68 of 80).

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Only models sharing at least one published sub-eval are listed.

Official and reference links

Published eval results

Rank is within that sub-eval. Black marks the observed result; the grey dot marks the value implied by the global rank. Values stay on each source’s native scale.

Eval / sub-evalRankValueDistributionBetterSource
AIRBench 2024 Safety Scenariossafety_scenarios#68 / 800.452↑ higherSource ↗official
Confabulationsconfabulation_rate#31 / 5226.24↓ lowerSource ↗official
Enkrypt AI Safety Leaderboardbias_attack_non_success_rate#97 / 26019.12↑ higherSource ↗official
Enkrypt AI Safety Leaderboardcbrn_attack_non_success_rate#46 / 26092.67↑ higherSource ↗official
Enkrypt AI Safety Leaderboardharmful_attack_non_success_rate#45 / 26092.78↑ higherSource ↗official
Enkrypt AI Safety Leaderboardtoxicity_attack_non_success_rate#105 / 25897.27↑ higherSource ↗official
HELM Safetyanthropic_red_team#50 / 800.983↑ higherSource ↗official
HELM Safetybbq#11 / 800.969↑ higherSource ↗official
HELM Safetyharmbench#23 / 800.885↑ higherSource ↗official
HELM Safetysimple_safety_tests#58 / 800.97↑ higherSource ↗official
HELM Safetyxstest#24 / 800.97↑ higherSource ↗official
HUMAINE Trust, Ethics and Safetytrust_ethics_safety_score#41 / 5425.53↑ higherSource ↗official
Large-scale Moral Machine experiment on LLMshuman_choice_distance#1 / 390.7105↓ lowerSource ↗official
SORRY-Benchavg#20 / 510.24↓ lowerSource ↗official

Values evaluations

Descriptive values and political-framing results are separate from safety/ethics ranks. Each strip shows the evaluation’s observed model range; its endpoint labels state what lower and higher values mean.

ValueCompass

DimensionValueDistribution
Universalism62.5
Self-direction46.5
Care / Harm47.6
Fairness / Cheating43.5
Ethical90.8