
Open source alternatives to Jev
Laya, OpenJev, Kev and the other open-weight decision models, with the local runtimes, ports and benchmarks their authors published.
177 builds · page 6 of 6
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GitHubOpen source
RSI-Jev
Decision models trained by a self-improving loop of AI agents.
Shanghua Gao
113

2BParameters
Strands Agents
6Models at launch · 5 ms laya, one question · 43 ms openjev 27b, one question
ggml-org

35,812Jev calls logged · USD 3.68 jev total cost · 44% untrained laya · 94% jev
ArticleBenchmarks and evals
Laya in shadow, next to Jev on every request
Kitsuno trains an open model to replace Jev in production.
Kitsuno
$0.038Clef-flash, per M input tokens · about 130 ms text-only decision, median
ArticleOpen source
Clef-omni, a faster Clef and a cheaper Clef-flash
Cloudflare's open-weight decision model now takes audio and video.
Cloudflare

doofz
@reversedoofz
WAIT. An open-source decision model with 322M parameters that beats Jev on some benchmarks... Runs locally on a PHONE... And now has a FREE API?! Meet THX-01. Weights: huggingface.co/doofz/THX-01 API (Free): api.hal-x.ai/docs/thx-01 pip install thx01

Rhythm Garg
@rhythmrg
You can now train your own decision model in our platform AC2! Jev-like models, custom fit for your use case :) We implement decision models through a language-model backbone with a small learned output layer called a decision head. The backbone processes the input, question, and answer choices, and the head produces scores which are softmaxed to produce a probability distribution over answer choices. Our software interface makes it easy to add a variable-sized decision head to frontier open-weight models. Choose any open source model, and train it as a decision model using Brier loss or cross-entropy loss. Training updates both the decision head and the language backbone. We tried it on 50k sampled training datapoints from the Civil Comments dataset, starting from Perplexity’s pplx-decider-v1-27b, and F1 for detecting toxic comments increased from 0.482 to 0.677 on 20k sampled eval datapoints. The training job took less than an hour on four B300 GPUs. Reach out to get started with your own classification task: https://docs.appliedcompute.com/platform/training/decisions
GitHubOpen source
local-jev
An offline drop-in for the Jev API, as one Rust binary.
ronitgupta138
1< 18msGitHubOpen source
Dex
An open-source, Jev-compatible decision model on an Ettin-1B encoder.
CanadaOrNaw
171.4%