Jev is Vercel’s fastest-adopted AI model ever

Jev has become the fastest adopted AI model ever — at least by some measures. Vercel data published on Thursday shows that, within two weeks of its launch, the buzzy decision model was being used by 35% of paid teams, with nearly double the reach of the second most popular model, Sonnet 5.5. It’s the fastest adoption a model has ever seen in its first two weeks, according to Vercel’s data, and a major accomplishment for the model’s creators, TypeSafe AI.

Jev 已成为有史以来采用速度最快的人工智能模型——至少从某些指标来看是这样。Vercel 周四发布的数据显示，在该决策模型发布后的两周内，已有 35% 的付费团队开始使用它，其覆盖范围几乎是第二大热门模型 Sonnet 5.5 的两倍。根据 Vercel 的数据，这是模型在发布前两周内实现的最快采用速度，对于该模型的创建者 TypeSafe AI 来说，这是一项重大成就。

Published in limited release on September 15, Jev is designed as a lightweight tool for choosing between a few predetermined outputs. Limiting the outputs lets the model run cheaper and faster than alternatives like Sonnet, making it ideal for classifying large quantities of data quickly. That new approach has attracted significant buzz in the weeks since Jev’s release — inspiring competing offerings from OpenAI and Amazon, among others — but until now there has been little hard data to back up the good vibes.

Jev 于 9 月 15 日限量发布，旨在作为一种轻量级工具，用于在几个预定的输出结果之间进行选择。限制输出结果使得该模型比 Sonnet 等替代方案运行得更便宜、更快捷，非常适合快速分类大量数据。这种新方法在 Jev 发布后的几周内引起了极大的轰动，并激发了 OpenAI 和亚马逊等公司的竞争性产品，但在此之前，几乎没有确凿的数据来支持这些良好的市场反响。

The data comes from Vercel’s AI gateway, a unified API service similar to OpenRouter. It’s a necessarily limited view — particularly at risk of undercounting major labs like OpenAI and Anthropic that offer their own APIs — but it shows the buzz around Jev really did translate into actual usage. In fact, Vercel was an early adopter of Jev, using it to replace GPT-6 Luna for classifying harmful commands.

这些数据来自 Vercel 的 AI 网关，这是一种类似于 OpenRouter 的统一 API 服务。这是一个必然受限的视角——特别是存在低估 OpenAI 和 Anthropic 等提供自有 API 的大型实验室的风险——但它表明围绕 Jev 的热度确实转化为了实际使用。事实上，Vercel 是 Jev 的早期采用者，使用它取代了 GPT-6 Luna 来分类有害指令。

The report also shows continuing momentum for open source models, which now account for more than 70% of the tokens processed through Vercel’s gateway and nearly 25% of the total spend. While open source models are capturing a larger share of the market, the market is also growing fast. Spending on frontier labs has grown tenfold, even as it accounts for a smaller share of overall spend, giving credence to the idea that frontier models and open source alternatives may turn out to be complementary rather than competitive.

该报告还显示了开源模型的持续增长势头，目前它们占通过 Vercel 网关处理的 Token 总量的 70% 以上，占总支出的近 25%。虽然开源模型正在占据更大的市场份额，但市场本身也在快速增长。对前沿实验室的支出增长了十倍，尽管其在总支出中所占份额较小，但这证实了前沿模型和开源替代方案最终可能是互补而非竞争关系的观点。