What qualifies for the Benchmarks & research category?
Entries include datasets, evaluation harnesses, comparison studies, research prototypes, measurements, and reproducible experiments involving Jev.
Explore an awesome collection of 99 verified open-source Benchmarks & research Jev projects on bestjev. Compare GitHub stars, languages, repositories, and implementations.
Open 0.6B Jev replica with parallel decisions, complete probability distributions, training pipeline, weights, dataset, and live demos.
Train a small model that chooses among a changing list of text options, one probability per option in a single pass. Includes Doom, chess, and Wikispeedia demos.
An educational Jev-like visual inference experiment on Apple Silicon: shared context, direct candidate scoring, and local visual demos.
One-pass typed decisions with calibrated probabilities (System One style model), fine-tuned from Qwen3.5-2B.
Personal-assistant agent built on Vercel's eve with 100 mocked tools, measuring how many steps it takes when Jev picks the tool versus the LLM.
A small open decision model: state + typed questions -> calibrated probabilities. A Jev / System One re-creation on Qwen3.5.
WebMCP benchmark comparing browser-agent interfaces, with Jev included as one of the evaluated configurations.
JevBench v1 - a benchmark for Jev-class typed decision models: smart, cheap, fast, reliable, open.
One-pass option scoring with a local Gemma 3 4B on Apple silicon via MLX, inspired by jevlike, with a Doom demo.
Jev-style parallel constrained decisions for any MLX model on Apple Silicon. Typed, schema-valid JSON in one forward pass.
This is a LLM Gateway that mimics typesafe ai structured output. Like an imposter Jev.
Non-autoregressive decision engine on ModernBERT (151M) with calibrated uncertainty (RLCD), TypeSafe AI Jev benchmark audit, and in-browser WebGPU playground.
Mini-Jev: what a Jev-style typed-decision interface looks like on a frozen Qwen3-4B — read the option letter's logits instead of generating JSON. Preregistered experiment, results, teaching bench.
A reproduction of Jev that turns any Qwen model into a fast decision model, serving the same /v1/systemone schema (Choice, Score, Noul) with no training and no generated answer text.
Unofficial study: Jev-style parallel typed decisions on stock 1.5B-8B models on an Apple Silicon laptop. Benchmarks, research notes, and a Hugging Face Space demo.
Jev vs Gemini 3.8 Flash: labelling 1,000 app reviews, 4.1× faster and 7× cheaper.
Benchmarks and research evaluate Jev behavior, decision quality, calibration, performance, and practical tradeoffs.
Entries include datasets, evaluation harnesses, comparison studies, research prototypes, measurements, and reproducible experiments involving Jev.
Entries include datasets, evaluation harnesses, comparison studies, research prototypes, measurements, and reproducible experiments involving Jev.
Start with the documented use case, repository activity, primary language, license, and visible Jev implementation. GitHub stars are a dated discovery signal, not a quality score.
bestjev checks public repositories, project-authored documentation, code, demos, and other visible evidence. Always confirm current behavior and compatibility in the upstream project.
bestjev grounds this category in named primary sources: Official Jev documentation · Public GitHub repositories.
“Typed outputs that software can act on.”— TypeSafe AI