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.
Jev Doesn't Write Answers, It Picks the Next Move
Jev is a decision model, not a chat model: it doesn't generate answers but picks the next move, such as routing tickets, skipping review, or marking changes low-risk.
#Jev does not write the answer. It picks the next move. That is a different object to evaluate. A chat model can be wrong in public. A decision model can be wrong and still open the gate: route the ticket, skip review, click buy, mark the change low-risk. The output is a
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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.
