客户提案现场用 Jev 做模型路由决策
演示面板里 Jev 从 214 个模型中挑出图像模型并给重跑把关，把人工选型、评分、重跑三道流程从秒级压到 0.2ms，单次决策成本降到 $0.0001。
I ran a routing decision through JEV for a client pitch, and the cost readout landed at $9.32 saved before I even finished explaining what the dashboard was showing. 214 models lit, 26 currently warming, 268 decisions logged, cost per decision sitting at $0.0001, latency 0.2ms. The rule sat printed plainly in its own box: JEV picks a model, Picsart makes the asset, JEV gates the re-run, and the human says whether it's actually good. One prompt fired into the prompt bar and radiated straight out through the router as hundreds of thin lines, ima_28 landing as the routed image model, picked by JEV at 3.45 credits, snapshot logged and stamped as "routed" the instant it resolved. Feed underneath kept scrolling live, route, gate, judge, score, each decision tagged with its own credit cost, none of them silent. The number that actually closed the deal was in the comparison table at the bottom: picking a model manually used to run 2.1 seconds, scoring against a brief 1.8 seconds, gating a re-run 2.4 seconds, JEV collapsed all three to 0.2ms each. Cost per call dropped from $0.030 to $0.0001. Full re-run avoided far more often than a re-run got triggered. That's the part I didn't need to explain twice. 214 models, one prompt bar, and a dollar figure sitting in the corner proving the routing decision paid for itself before the client asked a single follow-up question.
这条是引用着另一条写的：x.com/blazt_ai/status/2102767421895389346