Vercel data shows Jev hits 35% adoption in two weeks
Vercel’s internal data reveals its AI model Jev became the fastest-adopted model ever, reaching 35% of paid teams within two weeks of its September 15 launch. That exceeds Sonnet 5.5’s reach by nearly double, according to Vercel’s AI gateway metrics. Jev specializes in lightweight decision-making between predefined options, running faster and cheaper than alternatives like Sonnet, making it…
Key points
- Jev reached 35% adoption among Vercel’s paid teams in two weeks, surpassing Sonnet 5.5’s reach
- Designed for fast, low-cost decision-making between predefined options, replacing GPT-6 Luna for Vercel
- Open-source models now account for 70% of tokens and 25% of spending on Vercel’s AI gateway
The report also underscores growing open-source adoption: 70% of tokens processed through Vercel’s gateway now use open-source models, with 25% of total spend tied to them. Meanwhile, spending on frontier labs has surged tenfold, suggesting complementary rather than competitive trends. Vercel’s data excludes major labs like OpenAI and Anthropic, limiting its scope but confirming Jev’s real-world traction.
Model pages: Jev → · Sonnet 5.5 → · GPT-6 Luna →
The story so far
3 episodes →- Vercel data shows Jev hits 35% adoption in two weeksthis story
Jev is Vercel’s fastest-adopted AI model ever
TechCrunch AI · 16 October 2026
Loading the full article…
This text was published by TechCrunch AI and written by Russell Brandom. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗
The headline, key points and digest above were generated by Digest AI's editorial model from the linked sources. Automated summaries can contain errors: the sources are the record. Spotted a mistake? Tell us. Published by Martin K., who runs Digest AI and handles corrections.
More in Generative AI & Models
All →- Elorian releases Glimpse, a visual reasoning model with API access · 1 src
- Reflection releases open-weight Beam 1.0 with 501B parameters and 1M-token context · 4 src
- Google launches Gemini 4 Argon model globally for Pro and Ultra subscribers with introductory API pricing · 33 src
- Imperial College study finds LLMs cite unread pages, raising accuracy concerns · 1 src
- Microsoft AI chief says in-house model beats OpenAI's using quarter of compute · 2 src
Comments
via GitHub Discussions