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 p

🇬🇧 Summary in English

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

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Fonte: TechCrunch | Argomento: Intelligenza Artificiale

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