jevbooks

← All projects

typed-decision-bench

4nt0ineB/typed-decision-bench

Bench of typed decision models: Jev vs OpenJev vs Laya, small local LLMs and cheap hosted LLMs on the same zero-shot classification tasks, in English and French.

Evaluation & Benchmarking0.85Runner-up: Classification & RoutingQuestionnaireCheck-up
Automated README summary

Automatically summarized from the README on 30 Sept 2026; not a run by jevbooks. Run instructions and author-reported outcomes still need verification.

What it is

A benchmark comparing Jev, OpenJev, Laya, small local LLMs and cheap hosted LLMs on zero-shot classification tasks in English and French, using hand-written options and criteria, no labelled data, no fine-tuning.

How it uses Jev

Jev is used zero-shot: given a state (message, JSON, document) and typed questions with options and criteria, it returns a probability per option. Results are stored as raw JSON under results/ and bench/report.py rebuilds tables and charts without calling a model.

Primitives:choice

Technique worth stealing

Zero-shot classification with typed questions and per-option criteria, evaluating calibration and automation at thresholds.

View on GitHub

Start using Jev: API key and your first request →

Model judgments from README excerpts

Project signals use repository metadata, an existing summary and the first 700 README characters, not the full project. “Not found” means not detected in that material; it does not establish absence. These are the original judgments with recorded models and dates, not source audits or run results.

Models & evaluation dates

Inclusion gate
jev-1.13.0
Project signals
jev-1.13.0
Category
jev-1.13.0
Pattern tags
jev-1.13.0

Evidence

These signals use repository metadata, an existing summary and at most 700 cleaned README characters. ≥ 0.60 means reported in that excerpt; ≤ 0.40 means not found there. The middle band is inconclusive. None is a source-code audit or a test result. The runnable-tool question excludes research experiments; the recommendation question asks for a learning shortlist, not a quality verdict.

  • Jev is core to the projectnot found in the excerpt0.39
  • Shows a System One patternFound in material0.66
  • Describes handling uncertaintyFound in material0.91
  • Reports measured numbersnot found in the excerpt0.07
  • Is a runnable toolnot found in the excerpt0.09
  • Top-10 learning shortlist signalnot found in the excerpt0.26
  • Is a replica of the modelnot found in the excerpt0.07
  • Solves a common problem (0–2)score on a 0–2 scale1.18 / 2
  • About JevFound in material0.98
Signals
Jev is core to the project0.39Shows a System One pattern0.66Describes handling uncertainty0.91Reports measured numbers0.07Is a runnable tool0.09Top-10 learning shortlist signal0.26Is a replica of the model0.0700.51Solves a common problem (0–2)1.18 / 2012

no-judgment band (0.40–0.60)

Design patterns
Questionnaire0.96Check-up0.85Flight recorder0.68Traffic light0.55Funnel0.5100.51

no-judgment band (0.40–0.60)

The Jev model and date for each judgment stage are listed above. Card written by DeepSeek V4.1 Flash from the README on 30 Sept 2026.