TypeSafe AI 推出 AI 模型 Jev,跳过逐 token 生成,速度比 LLM 快 20-200 倍、成本低 40-400 倍(输出 token 免费),响应时间 70-500ms。Jev 专为软件决策设计,输入数据和预设问题后直接返回带概率与置信度的类型化选择或分数,而非生成文本。它可并行评估多个结构化问题,在代码中像智能 if 语句,由普通软件控制流程、模型处理模糊判断。
Another brilliant launch for developers: and its 20-200x faster than LLMs because it skips token-by-token generation entirely.
TypeSafe AI just launched Jev,
> 20-200x faster
>40-400x cheaper (w/ output tokens free)
> Frontier composable intelligence optimized for decisions
So Jev is an AI model built to make software decisions instead of writing text for people.
A normal LLM answers by generating tokens sequentially, so software often has to request structured output, parse it, validate it, and decide what happens next.
Jev removes that translation layer: give it some data and a predefined question, and it returns a typed choice or score with probabilities and confidence.
For example, a support app can ask whether a ticket is urgent, whether it violates policy, and which queue should receive it, then act on those answers directly.
In code, Jev behaves like a smart if-statement: ordinary software controls the workflow while the model handles fuzzy judgments that rigid rules struggle with.
Jev evaluates multiple structured questions in parallel rather than writing an answer token by token.
TypeSafe reports 70-500ms responses and 40-200x faster performance than comparable LLMs
来源:@rohanpaul_ai · x.com