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-style decision model: JSON Schema instead of a question list
The model takes a JSON Schema instead of a question list, scores every independent field in one pass while dependent fields wait, and generation is per-field opt-in so the default never generates a token.
Here me out a Jev-style decision model that takes a JSON Schema instead of a list of questions one pass scores every independent field. dependent fields wait their turn. generation is a per-field opt-in, so the default never generates a token. You get back guaranteed
· 0 likesOpen on X
More like this
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.
