GoKawiilHybrid Jev-Opus model matches frontier accuracy at 4x lower cost
A team tested decision models Jev and Luna against the frontier model Opus on grading identity resolution results, a task that maps scattered data records to real-world identities. Used alone, Jev and Luna scored 88.8-97.3% accuracy, but a hybrid system letting Jev escalate uncertain cases to Opus matched Opus-level accuracy while cutting costs by more than 4x. The tests also found decision models run up to 90 times cheaper and 10 times faster than Opus, though they lag Opus by about 6 percentage points on harder cases.