Jev as judge vs LLM as judge: 100 agent trajectories benchmarked
On the same 100 agent trajectories, Jev took 13.5 seconds and cost $0.0019 versus GPT-5.5's 120.8 seconds and $0.419, about 9x faster and 219x cheaper, with a video showing each score.
Jev as a judge vs. LLM as a judge: We ran the same 100 agent trajectories through both evaluators. Jev finished in 13.5 seconds and cost $0.001912. GPT-5.5 took 120.8 seconds and cost $0.419130. That made Jev roughly 9x faster and 219x cheaper in this run. The difference comes from the job each model performs. A general-purpose LLM generates a judgment token by token. Jev is built to return focused, typed judgments and probabilities against defined criteria. The video shows the comparison live, including the score returned for every trajectory. We wrote a deeper breakdown of how Jev works as an agent judge, where it fits, and how to build with it. Read it below.
This post quotes another post: x.com/703601972/status/2102087107410002345