Two runners race through the same maze. Each step, a model looks at the board and picks a direction. On the left, Jev decides in about 100ms. On the right, a normal LLM makes the same decision, but takes over a second each move. Same task. Watch what happens.
Jevdecision modelready
0moves
–ms / move
0.0selapsed
LLMgptready
0moves
–ms / move
0.0selapsed
The LLM side is capped at a few moves so it stays cheap. Each move is a real API call to both.
Why it wins: it knows when it's unsure
Jev doesn't just decide fast. Its confidence is honest, so you can trust it. Try a review, clear or genuinely mixed.
Jev
confidence–
LLM
confidence–
And the confidence is calibrated
Score a labeled set, half clear reviews, half deliberately mixed. Jev is never told which. Its average confidence drops on the mixed ones by itself.