# Kev

> Apache-2.0 tiny Jev-like decision models you train and serve locally

**Category:** AI Agents  
**Pricing:** open-source  
**URL:** https://github.com/jaredpalmer/kev  
**GitHub:** https://github.com/jaredpalmer/kev  
**Added:** 2026-09-22

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## The Hook

Kev is a family of small Jev-style decision models (0.8B/4B/9B on Qwen3.5) you can train and serve yourself for yes/no, choice, and score tickets.

## What's Good

Apache-2.0 (jaredpalmer/kev). Pretrained weights, training code, frozen eval suites, and a local serve path (`uv sync --extra serve`) that speaks a System One-compatible API so TypeSafe's Python SDK can point at your box. CUDA/ROCm/Apple Silicon notes; HF Spaces demo for trying order-sensitivity without an install. Useful when agent loops need cheap structured decisions instead of another LLM judge call.

## The Catch

Vs jevals/TypeSafe Jev cloud and ordinary LLM-as-judge evals: Kev is the self-host decision-model family + training repo, not OpenLayer's jevals product wrapper and not a free hosted Jev API. 4B/9B want serious local VRAM/RAM (README cites ~32 GB Mac bf16 class for larger models); first serve downloads base + adapter weights. Decision quality still depends on your question design and calibration — local does not mean calibrated for your domain.

## Verdict

Apache-2.0 self-host Jev-like decision models. Keep when you want typed agent decisions without paying per LLM-judge call; budget GPU/RAM honestly.