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Fortune: Jev's viral hit and OpenAI's fast follow
Fortune reports Jev went viral among developers, with nearly 13% of Vercel's paid teams trying it within a day of its gateway arrival. Three weeks after Jev's launch, OpenAI rolled out a competing Decisions API built on GPT-6 Luna.
- Format
- Article
- Reading time
- 2 min
- Published by
- Community
- Author
- Wen Shao
- Last verified
- Oct 2026
Highlights
- Nearly 13% of Vercel's paid teams tried Jev within a day of its arrival on Vercel's AI Gateway, per the report.
- Vercel said Jev reached more than twice as many paid teams in its first 24 hours as any previous model launch.
- On Oct. 6, just three weeks after Jev's launch, OpenAI rolled out its competing Decisions API, per Fortune.
- OpenAI's Decisions API uses GPT-6 Luna, an existing model, while TypeSafe trained Jev specifically for this work.
- Dext's head of applied AI, Paolo Rosson: you pay for a full written answer when all you need is a label.
Watch out
Copy reviewed against the published article on 2026-10-17. The Vercel adoption figures are Vercel's own, TypeSafe's speed and cost claims are the company's, and the developer anecdotes are early experiments rather than independent benchmarks.
Questions about this entry
Short answers drawn from the linked project or page.
It documents the speed of Jev's adoption among developers, with nearly 13% of Vercel's paid teams trying it within a day, and OpenAI's response: a competing Decisions API rolled out three weeks after Jev's launch.
Within a day of arriving on Vercel's AI Gateway, nearly 13% of its paid teams had tried Jev, and Vercel said Jev reached more than twice as many paid teams in its first 24 hours as any previous model launch.
The Decisions API, rolled out on October 6, which uses GPT-6 Luna, an existing model in OpenAI's lineup, rather than a model trained specifically for classification decisions like Jev.
They take more computing power for classification than simple machine learning models, making them slower and more expensive. When a model must handle thousands of requests a day, the cost and delay of each call add up.
Almeida initially thought making the models behind Jev reliable would take him a week. Instead, TypeSafe spent two years developing Jev, and he told Fortune that making the models reliable was so much harder than expected.
Dext's Paolo Rosson estimated Jev's calls at seven cents per 1,000 changes, Aaron Roy saw important emails slip through until he replaced generic prompts with specific questions, and Niels Mouthaan was impressed by its speed.
Almeida wrote in TypeSafe's launch post that Jev is named for economist William Stanley Jevons, whose paradox held that more efficient steam engines would increase overall coal consumption by making coal-powered work cheaper.
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