为什么我用 Jev 比 Opus 5.5 和 GPT-6 还多：决策模型五个实战项目

“The other thing that you will notice about Jev is it is cheap AF and it is fast AF.”

你还会注意到 Jev 另一点：便宜到离谱，也快得离谱。

“Jev only charges you on input tokens 'cause it barely outputs anything, and it is four cents per million input tokens.”

Jev 只收输入 token 的钱，因为它几乎不输出，价格是每百万输入 token 4 美分。

“it's, it's great for things where you need stuff generated, but Jev is really great for making decisions.”

凡是需要生成内容的场景标准大模型都好使，但 Jev 真正擅长的是做决策。

“this is like 90% of software engineering is like doing these things, returning a choice, scoring something, routing, saying yes or no.”

软件工程 90% 的工作就是做这些事：返回选项、打分、路由、判断是或否。

“Jev with an LLM buddy is super powerful.”

Jev 配上大模型搭档，就超级强大。

“I like to take a big corpus of information, tag it, categorize it, cluster it, filter it, and then apply really precise AI actions to the right clusters.”

我喜欢拿一大坨信息，打标签、分类、聚类、过滤，然后对正确的聚类施加精准的 AI 操作。

“And until then, it has been so nice showing you my favorite new model.”

在那之前，很高兴向大家展示了我最喜欢的新模型。