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.
User tests Jev's choice logic
A user asked Jev to pick apple or orange for 'banana' and got apple; after asking it to check each option, Jev said neither, leading the user to conclude the multiple-choice question was flawed.
asked jev to pick apple or orange for 'banana'. apple. asked it to check each option instead. neither. my multiple-choice question was the problem.
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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.
