22 分钟实测：Jev 决策层 vs Opus 生成层
前 Google 工程师在真实 agent 里跑 Jev，实测比 Opus 快 10 倍、便宜 146 倍，但准确率并非总是最优，需要推理的场景仍得用传统 LLM。
One model for everything is the mistake. jev splits deciding from generating, and the test proves it In this free 22-min breakdown ex-Google engineer actually tests it inside a real agent instead of trusting the launch post: 01:27 - system 2 (llm) vs system 1 (jev): the comparison setup 02:29 - 230ms latency, 10x faster than opus, 2 cents per 1,000 calls 14:47 - "jev is 2200x faster, 40-400x cheaper. let's verify that" 17:32 - the real test: 10x faster than opus, 146x cheaper 19:35 - "jev's accuracy isn't always the best. opus still leads on quality" 21:10 - "anything that needs real reasoning? still use traditional llms" Most agent stacks still ask one frontier model to generate, route, and verify on every single call Llms create. jev decides. code enforces This free 22-min breakdown beats most paid agent courses Save this before you add another llm call to your agent loop
这条是引用着另一条写的：「Jev 把路由打分验证做成决策层」