Benchmarks & Research for Jev — page 7

TypeSafe AI System One (Jev) task plugin for QuantumNous/new-api — native /v1/systemone, synchronous evaluation, token billing

MCP server and agent skill for the TypeSafe AI System One API (Jev): decompose a judgment into Choice / Score / Noul questions, lint them, measure on labelled data, and put calibrated thresholds in code

Jev (TypeSafe) exploratory thread: claim audit, live demos, and runnable code

Not every coding task needs your best model. Experimental Jev-powered model routing for Claude Code — V3 prototype runs today, V4 routes at the task boundary.

Reward-hack radar for coding agents: structural denies + TypeSafe Jev System One sidecar for Claude Code & Cursor hooks

Independent Jev 1.13.0 behavior study: report, controlled prompt experiments, raw results, and offline verification.

Eight minimal working examples of TypeSafe's Jev (a System One model) applied to mechanical and electrical engineering: CAD/CAE/CAM routing, FEM result triage, DFM screening, BOM alignment, hallucination-proof extraction. Zero dependencies.

Blind security benchmarks for Jev, TypeSafe's System One model: prompt injection and vulnerable code detection, built on jev-go

Creating system one model just like jev. with different experimentation

Ne yazarsanız yazın, beş kelimeden biriyle cevap veren sohbet botu. Kelimeyi TypeSafe AI'ın Jev evaluation modeli seçer.

Benchmark of TypeSafe's Jev against Sonnet 5, GPT-5 nano and local LLMs on 770 Reddit AITA verdicts: Brier scores, latency and cost

JEV-powered market decision bot for stocks, crypto and memes. State in, BUY/SELL/HOLD/AVOID out, paper by default

Deep research crawl where Jev (a System One model) makes every per-page decision and an LLM only plans and writes

Real-world Jev use cases, open-source projects, benchmarks and criticism — what people actually build with TypeSafe AI's Jev, and where it fails. Machine-readable, updated daily.

MCP server for Jev (TypeSafe System One): the three official question types — choice, score, noul — plus batch classify. Calibrated probabilities, ~0.5s, <$0.001/call.

Grade the agent sessions already on your disk. Claude Code, Codex, opencode, Gemini CLI and Antigravity, scored with Jev for cents.

JevGym is an open-source platform designed to benchmark and facilitate better probabilistic estimation in Jev-alike models

Windows port of Laya typed-decision AI (ONNX Runtime + DirectML) — Core ML/Apple Neural Engine alternative with first-class Arabic support. No text generation, no hallucination, runs on any DX12 GPU.

Metask-Jev: calibrated typed-decision models (Jev-class). Single forward pass, candidate-logit readout. metask-jev-4b beats Bespoke Nimble-9B and Jev on JevBench.

Pytest plugin for semantic assertions on LLM output using Jev's calibrated probabilities.

Offline $0 decision layer for coding agents: Choice/Score/Noul primitives, BELKI confidence gatekeeper, ultra-planning, red-teaming, research and RLVR self-improvement -- as an MCP server + CLI + Claude Code skill.

A streaming event bus whose routing, subscription and consumption are decided by a probabilistic judge. The reference judge is TypeSafe AI's Jev (System One) model: send it a payload and a set of typed questions, get back calibrated probabilities instead of prose.

Sub-100ms security gate for AI agent tool calls, powered by TypeSafe's Jev (System-1) decision model. Single-request Choice/Noul/Score evaluation, dual-factor blocking matrix, calibrated-confidence routing, fail-closed parsing, zero-config local fallback. LangChain-ready.

MCP server exposing TypeSafe's Jev model as a typed evaluate tool.