Context Reasoning

Context understanding and reasoning tasks test accurate answers grounded in provided context. This capability is essential for knowledge-base support bots, policy lookup systems, and internal knowledge Q&A applications. Models are evaluated on their ability to provide accurate answers that are properly grounded in the given context rather than hallucinating information.

100
Duration
3s
Input Tokens
7592
Output Tokens
704
Cost
$0.00
Context
Input
Which patient had a more dangerous medical timeline?
Expected output
Melisa Farrow
Model output
Melisa Farrow had a more dangerous medical timeline. Her initial symptoms progressed rapidly to acute community-acquired pneumonia (CAP) involving the left lower lobe and pleural effusion. This required immediate transfer to the hospital for inpatient treatment, including IV antibiotics and temporary supplemental oxygen due to low oxygen saturation (93%). In contrast, Oscar Jansson was diagnosed with mild persistent asthma exacerbated by a viral infection, which was managed entirely on an outpatient basis with inhaled and oral medications.