The open-source System One decision model. Sub-15ms, non-autoregressive, local drop-in alternative to TypeSafe Jev.
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Updated
Oct 17, 2026 - Python
The open-source System One decision model. Sub-15ms, non-autoregressive, local drop-in alternative to TypeSafe Jev.
🔥🔥 Awesome Jev: open-source models, projects, benchmarks, and independent evaluations for Jev and System One models.
Calibrated 151M Non-Autoregressive Decision Engine beating TypeSafe Jev & Laya on LocalLLaMA/typed-decisions (77.10% acc, 0.0636 Brier, 0.0144 ECE)
Non-autoregressive decision engine on ModernBERT (151M) with calibrated uncertainty (RLCD), TypeSafe AI Jev benchmark audit, and in-browser WebGPU playground
Dohnuts builds small multimodal models for direct decisions. -> System One model
Claude Code/Codex skills and learning resources that make it easy to build with Jev, TypeSafe's System One model. All materials pull directly from their canonical cookbooks and documentation.
⚡ Foq — the FREE, local, open-source alternative to Jev. Typed System 1 decisions in ~25 ms — no waitlist, no cloud, no per-token cost. foq.fr
NIRNAY 450M: open-weight calibrated decision model (Apache-2.0). Banking77 intent classification 87.9%, fitted ECE 0.045. Laya fork plus concept bottleneck, coarse-to-fine pointer and RLCD. Built by Eulogik.
A MicroPython Driver for the Waveshare ESP32-S3 4.2inch RLCD display
A simple desk clock built around the Waveshare ESP32-S3-RLCD-4.2 — a 4.2" reflective LCD (e-paper-like) development board.
Fine-tune Laya, the open System One decision model, for any typed-decision task: synthetic data, RLCD, calibration and long context.
A TypeSafe-native (Jev) coding agent built on Recursive LLM Context Decomposition (RLCD), with a native macOS client
ESP32-S3 RLCD desktop display for Codex quota, room sensor data, battery status, and a mood pet synced over BLE.
1,000-decision behavioral benchmark of Jev across 25 deterministic reasoning families.
Lightweight, non-autoregressive System 1 decision model showcase for instant text classification, calibrated urgency scoring, and triage using Hugging Face Transformers and Laya
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