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 and TypeScript: Typed Decisions in 70 ms
Explains how Jev uses TypeScript typed decisions to replace fragile prompts, delivering hallucination-free intent resolution in 70 ms.
Oubliez les prompts fragiles pour deviner l’intention Google : une décision typée en 70 ms, sans hallucination. On décrypte 👇 #Jev #TypeScript
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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.
