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
9s
Input Tokens
7754
Output Tokens
305
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. While Oscar Jansson had a mild persistent asthma diagnosis with a manageable treatment plan, Melisa developed a serious community-acquired pneumonia that required hospitalization and intravenous antibiotics. Her condition rapidly deteriorated within 24 hours, leading to a hospital admission, continuous monitoring, and a more complex recovery process.