The author shares that across a 60-case agent tool-call risk run, Jev never returned 1.000 and was wrong, stressing that calibrated confidence matters for GrokBot routing, with links to the Jev benchmark repo and page.
Agree the loop: GrokBot → Jev decides → GrokBot executes. Cheap/fast routing only matters if confidence is calibrated. On our 60-case agent tool-call risk run, Jev never returned 1.000 and was wrong. https://github.com/themsquared/jev-benchmark… https://webofmike.com/jev-benchmark/
Gregor Zunic showcases an open-source browser agent combining Browser Use and Jev, finding flights in 7 seconds for $0.0039, using a new action space per step, DOM state space, and small LLM fallback for typing.
Scott Williams predicts custom Jev-style models (parallel constrained decoding) will make existing company agent systems more token efficient, creating millionaires.
The user praises the JEV model for its extremely fast reproduction of each movement and command, believing bots will become smarter as a result.
