Jev versus text-generating models
Jev does not generate free-form text. A side-by-side video compares parallel decision-making with token-by-token text generation.
How JEV Works, Simplified
A user shares initial experience with JEV, explaining how it makes decisions based on provided information, questions, and the type of answer needed.
here's how JEV works, simplified I've been experimenting with it for the last hour, and it's EXTREMELY good at making decisions with the right references and context you give it the information, your questions, and the type of answer each question needs: > a choice from
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Pricing, evaluations, and the name Jev
The launch thread explains code-and-AI workflow evaluations, the input price announced at launch, and free output tokens.
Jev Model: Decision-Making Probability Generation, 200× Faster and 400× Cheaper Than LLMs
This model is built for decision-making rather than text generation, outputting probabilities for each option in parallel instead of token-by-token responses. The author shares a simplified comparison of normal LLMs versus this Jev model.
