Our summary
Arize compares eight decision models as judges of other AI systems. Each selects supplied answers rather than writing an explanation. The tests cover false information, general evaluation questions and agent task routing, measuring accuracy, speed, cost and whether confidence lines up with correctness.
The final comparison puts Jev and Kev in a tie. In a separate test, Arize reverses a question's meaning while leaving the task equivalent. Several models' rankings deteriorate sharply, while Jev, Clef 27B and OpenAI remain steadier. An overall score alone misses this sensitivity to wording.
These are results on Arize's chosen tests and instructions. It already integrates Jev into its product, the routing set contains only fifty-two cases, and Arize chose OpenAI's prompt layout. Those choices constrain the comparison; they do not establish a winner for every task.
Key takeaways
- Ask an equivalent question in positive and negative wording and compare the results.
- Alongside accuracy, speed and cost, check how confidence relates to correctness.
- The Jev–Kev tie applies to Arize's tests, not to a general leaderboard.