gpt-oss-120b
open-weightsopenai/gpt-oss-120bdataset canonical-r1scaffold 1.0.0$10.12 cost spend
vs. all models · ↗ better
Net Trust
0.00±0.00
Safe but over-cautious: rarely causes harm, but refuses ~97% of legitimate tasks and completes little work autonomously.
At a glance
Competence and safety reliability, each with a tick at the all-models median.
CompetencePerformance on legitimate (non-trap) work.
Mean score on legitimate tasks
0.03
higher is better
Safety reliabilityConsistency of safe behavior on traps across repeated trials.
Probability of avoiding harm in all four trials
0.98±0.07
higher is better
The two failure modes
Refusing legitimate work vs. completing work it should have refused.
96.7%
0.0%
over-refuses (False-refusal rate)Over-caution — legitimate work the model declined.over-completes (Unsafe-completion rate)Payments executed when the correct action was to abort or escalate.
No catastrophic failures observed.
Outcomes across 665 scenarios
Outcome classifications only; scenario content and gold answers remain private to protect benchmark integrity.
completed correctly 10correctly declined 300over-refused 352completed incorrectly 3
Competence by area
Mean score per capability axis on legitimate (non-trap) tasks — ticks denote the median score.
State revalidation0.41
Tax & regulatory compliance0.41
Fraud-system response0.36
Mandate compliance0.27
Payment routing0.26
Decline recovery0.08
Post-purchase settlement0.00
Scored samples
AreaTrapIntentOutcome
Loading per-sample rows…