Vercel: Jev Adopted by 35% of Paid Teams in Two Weeks

The usage statistics of Vercel's AI gateway indicate an unprecedented rise of Jev and a shift towards open source. Over 70% of the tokens processed by this service now come from open models, while Jev has reached 35% adoption among paid teams within two weeks. These figures come with methodological reservations related to the scope of Vercel's API.
Open source dominates in tokens and spending sees significant increase
According to Vercel, open source models now generate over 70% of the tokens processed by its gateway, accounting for nearly 25% of total spending. Meanwhile, budgets allocated to cutting-edge labs have increased tenfold, although they represent a smaller share of overall expenditure. Vercel suggests that cutting-edge models and open source alternatives could be complementary rather than competitive.
Data from a unified API, with a limited scope
The data comes from Vercel's AI gateway, a unified API service comparable to OpenRouter. This view remains limited and may underestimate players like OpenAI and Anthropic, which offer their own APIs. Vercel was one of the first to use Jev, employing it to replace GPT-6 Luna in the classification of harmful commands. The published metrics show that interest in Jev has translated into actual usage.
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Jev: limited launch, record usage, and technical positioning
Released in a limited version on September 15, Jev was designed to select a response from a few predefined outputs. This constraint allows the model to be less costly and faster than alternatives like Sonnet, making it suitable for ranking large amounts of data. Two weeks after its launch, 35% of paid teams were using Jev, with its reach nearly doubling compared to Sonnet 5.5. According to Vercel, no other model has experienced such rapid adoption in its first two weeks. Jev was developed by TypeSafe AI. Its release has generated significant excitement and inspired competing offerings from OpenAI and Amazon, while little concrete data has been available until now.
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