Jev 成为 Vercel 采用速度最快的 AI 模型

Jev 已成为采用速度最快的 AI 模型——至少按照某些衡量标准来看是如此。

Vercel 于周四发布的数据显示，在发布后的两周内，这款备受关注的决策模型已被 35% 的付费团队使用，其覆盖率接近第二受欢迎模型 Sonnet 5.5 的两倍。根据 Vercel 的数据，这是任何模型在发布前两周内所实现的最快采用速度，也是该模型开发者 TypeSafe AI 的一项重要成果。

Jev 于 9 月 15 日以有限发布形式推出，旨在作为一种轻量级工具，在少量预先确定的输出之间作出选择。限制输出选项使该模型能够以低于 Sonnet 等替代方案的成本、更快的速度运行，因此特别适合快速分类海量数据。自 Jev 发布以来，这种新方法在数周间引起了大量关注，并促使包括 OpenAI 和 Amazon 在内的公司推出竞争产品；但在此之前，几乎没有确凿数据能够佐证这种积极的市场反响。

这些数据来自 Vercel 的 AI Gateway，这是一项类似 OpenRouter 的统一 API 服务。它必然只能呈现有限视角——尤其可能低估 OpenAI 和 Anthropic 等提供自有 API 的大型实验室——但数据表明，围绕 Jev 的热度确实转化成了实际使用量。事实上，Vercel 是 Jev 的早期采用者，曾使用它替代 GPT-6 Luna，对有害命令进行分类。

报告还显示，开源模型的增长势头仍在延续：它们如今占 Vercel Gateway 所处理 token 总量的 70% 以上，并占总支出的近 25%。

尽管开源模型正在获得更大的市场份额，市场本身也在快速增长。前沿实验室模型的支出增长了十倍，尽管其在总体支出中所占比例有所下降；这进一步支持了一种观点，即前沿模型与开源替代方案最终可能是互补而非竞争关系。

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.

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.

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.

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.