Test de Jev (TypeSafe, jev-1.13) sur 3 373 plats à la carte.

@Fl0 Florian | FlowGrapher · Sep 20, 2026 · case #024823 · listed via Jev Hub

Still from the clip posted with this case; watch it in the original post on X.

Ran Jev over 3,373 menu dishes to classify cuisine type, measuring 84.5% agreement, 9.7s runtime, and $0.11 cost.

The original post

Test de Jev (TypeSafe, jev-1.13) sur 3 373 plats à la carte. Objectif : trouver le type (viande, pâtes, pizza, etc.) Résultat : 9,7 s, 2,56 M tokens in, 0,11 $, 84,5 % d’accord (406 désaccords, 116 incertains) Deux ratés parlants : Tagliata → pâtes Fondue vigneronne →

Engagement when collected

Likes0

Bookmarks0

Reposts0

Replies0

Quotes0

Numbers are a snapshot taken from X when the case was added to the library (schema v1, collected 2026-09-19); they will not match today.

Where this case fits

Filed under coding & developer tools. In the pattern Jev is built for, the model answers a bounded question per step — and ordinary code acts on the answer, because the answer is already a value rather than a paragraph. Other posts in the same family are on the coding & developer tools page.

🛠️ Coding & developer tools