The full directory
All Jev AI model resources
Entries for TypeSafe AI's flagship System One model — official docs and SDKs alongside community clients, tools, and write-ups.
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3919- Docs169
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All 3919 Jev AI model resources
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Showing 1777–1824 of 3919 resources
AutoTrust's Gemma-based decision model with adaptive thinking: System 1 answers below 0.8 confidence hand off to the full Gemma 4 26B and mix the two by half, behind POST /v1/decide.
Jev Models & Reimplementations#community#open-models#local
Community
Liquid AI's 3.12B decision model built on LFM2.5-VL: state plus typed questions in one forward pass with zero output tokens, 48.57 on Decision Index 0.2.1 and 8 ms per decision on an RTX 4090.
Jev Models & Reimplementations#community#open-models#local
Community
An untrained readout: stock Gemma-4-31B weights plus a decider config that reads option letters at the answer slot, scored #2 of 70 on Decision Index v0.2.1 at 57.33 against Jev 1.13.0's 57.91.
Jev Models & Reimplementations#community#open-models#local
Community
GGUF builds of the Jev-Style v3 decision model on Qwen3.5-0.8B: a 0.53 GB Q4_K_M file the card says is decision-identical to FP32 on 240/240 parity rows, served through a pinned llama.cpp scorer.
Jev Models & Reimplementations#community#open-models#local
Community
Interfaze's 4B LoRA adapter over Qwen3.5-4B that speaks POST /v1/systemone: 0.807 held-out weighted accuracy and 0.061 ECE after calibration, with a 200,000-example training recipe documented.
Jev Models & Reimplementations#community#open-models#local
Community
Nace.AI's 8B decision model on NVIDIA's Efficient-DLM diffusion backbone: a 256-dim pointer head scores every option in one pass, behind the same POST /v1/systemone API as its hosted service.
Jev Models & Reimplementations#community#open-models#local
Community
A 400M-parameter Jev-compatible decision model with a browser build: 0.796 on typed decisions against Laya's 0.766, 17 ms per question on an L40S, and an ONNX file that runs in a tab.
Jev Models & Reimplementations#community#open-models#local
Community
The vLLM Semantic Router project's 29.37B decision model on Qwen3.8-27B: a probability per supplied option with zero generated tokens, 74.0 on JevArena and 56.5 on Jev Decision Index 0.2.1.
Jev Models & Reimplementations#community#open-models#local
Community
Superagent's security triage model: a continual fine-tune of AutoJev-27B that returns calibrated probabilities for prompt-injection and content checks, with a release policy at 0.70 unsafe.
Jev Models & Reimplementations#community#open-models#local
Community
FINAL-Bench's zero-token classifier: one forward pass plus a fitted temperature produce a full distribution over options, scoring 0.743 on the 2,000-decision typed-decisions test split.
Jev Models & Reimplementations#community#open-models#local
Community
Strands Agents' small decider for agent plumbing: routing, tool selection, triage, and guardrails from a 2B LoRA checkpoint that serves /v1/systemone locally or through a Python package.
Jev Models & Reimplementations#community#open-models#local
Community
A 4B scorer rebuilt from Qwen3-4B into a branching cross-encoder: one branch per option, no position bias, up to 256 options, and calibrated probabilities with no text to parse.
Jev Models & Reimplementations#community#open-models#local
Community
A 706,048-parameter form-filling scorer from Cua AI: given a UI element and candidate options it returns one probability per option, including check, click, and skip actions.
Jev Models & Reimplementations#community#open-models#local
Community
A 0.4B Jev-compatible decision model with measured order invariance: 960 random option shuffles moved no probability by more than 1e-5, and bev-decider serve exposes /v1/systemone.
Jev Models & Reimplementations#community#open-models#local
Community
An ultra-light Italian decision model: 400M Llama-based, a 465 MB Q8_0 GGUF, answering multiple choice with A–D tokens and booleans with TRUE/FALSE for edge and Rust use.
Jev Models & Reimplementations#community#open-models#local
Community
The 400-case, 2,000-decision benchmark open models train and report against: four workflows, state plus typed questions, and gold distributions averaged from three teacher samples.
Jev Benchmarks & EvaluationsDocs#community#benchmarks#evaluation
Community
2.5 million typed decisions recast from 670 sources: choice, score, and noul rows with per-row licenses, soft annotator targets, and Jev-audited mix weights.
Jev Benchmarks & EvaluationsDocs#community#evaluation#calibration
Community
572,000 procedurally generated decision problems where labels are computed exactly from rules in the state: 13 task families, 4–60 options, and difficulty calibrated against Jev 1.13.
Jev Benchmarks & EvaluationsDocs#community#evaluation#calibration
Community
A native Brazilian Portuguese typed-decisions benchmark: seven choice and noul tasks over legislative, legal, scientific, and fact-checking text, with a tuned 4B model at 72.9% mean.
Jev Benchmarks & EvaluationsDocs#community#evaluation#calibration
Community
The 741,000-row distillation corpus behind AutoTrust's Jev students: choice, score, and noul rows with full target distributions across yuri and openjev source streams, Apache-2.0.
Jev Benchmarks & EvaluationsDocs#community#evaluation#distillation
Community
The official Laya playground: eight tabs that show choice, score, and noul decisions on ticket triage, phishing, guardrails, RAG filtering, moderation, routing, and multilingual text.
Jev Demos & ExperimentsPlayground#community#open-models#playground
Community
A ZeroGPU demo of Julia 1: define a state and any set of choice, score, and noul questions and see per-option probabilities rendered as bars and raw JSON.
Jev Demos & ExperimentsPlayground#community#open-models#playground
Community
An independent 2,018-item answer-verifier benchmark: the same items and labels for every entrant, each run on its own maker's code, with Jev, ZTC-Judge, Darwin, and open models ranked by weighted AUC.
Jev Benchmarks & EvaluationsPlayground#community#evaluation#benchmarks
Community
The System One Mosaic Benchmark leaderboard: about 100 decision models compared across 100+ specialized tasks, with results regenerated from a public dataset rather than estimated.
Jev Benchmarks & EvaluationsPlayground#community#evaluation#benchmarks
Community
macOS command palette that reads the frontmost app's menu tree through the accessibility API, asks Jev one Noul per menu item against a plain-language request, and presses the top match above a confidence threshold, falling back to a ranked list otherwise.
Jev Tools & CLIs#community#macos#command-palette
Community
rohit9mehta/dwimSwift
rohit9mehta/dwimSwiftPython harness for GUI grounding: it divides a screenshot into grid tiles, has a vision model describe each tile neutrally, then asks typesafe-ai/jev to choose among the descriptions. Local confidence and margin gates decide whether to descend or refuse, and it emits only a point and bounding box.
Jev Tools & CLIs#community#gui-grounding#computer-use
Community
ZihuaEvan/GUI_JEVPython
ZihuaEvan/GUI_JEVPythonClaude Code PreToolUse hook that asks Jev one Noul on whether a Bash command is strictly read-only and auto-approves at p of 0.95 or higher. It can only allow or stay silent, never deny, so unknown or risky commands fall back to Claude Code's normal permission prompt.
Jev Tools & CLIs#community#claude-code#hooks
Jev-style medical QA implementation on Qwen3.5-4B that selects an answer from candidates in one forward pass instead of generating text. It reports 69.42% accuracy versus 67.41% for standard generation and a 10.37x speedup across 153,889 questions from nine benchmark sets.
Jev Models & Reimplementations#community#medical#benchmark
Community
Ztrura/Jev-MedQAPython
Ztrura/Jev-MedQAPythonApache-2.0 ModernBERT fine-tune that answers noul, choice, score and multi-label questions with a probability for every option. It serves Jev's POST /v1/systemone locally so TypeSafe's Python SDK runs unchanged, reporting 0.026 expected calibration error on its test split.
Jev Models & Reimplementations#community#calibration#modernbert
Community
SamratDuttaOfficial/WaterSheepPython
SamratDuttaOfficial/WaterSheepPythonChrome extension that adds user-defined topic and expression labels to Weibo, Threads and X posts. It uses Jev Noul judgments against per-platform dictionaries, up to 60 labels per platform, and sends post text and label rules directly to TypeSafe under your own API key.
Jev Integrations & Adapters#community#chrome-extension#social-media
Community
SkywalkerDarren/feed-lensJavaScript
SkywalkerDarren/feed-lensJavaScriptClaude Code plugin whose UserPromptSubmit hook asks Jev a Choice over /effort levels (low, medium, high, max, unclear) plus a Noul on whether a hands-off request has a fuzzy spec, then offers a one-key switch before Claude starts when the tip clears its confidence threshold.
Jev Tools & CLIs#community#claude-code#plugin
Cloudflare Worker that asks Jev on Workers AI for literal profanity in text or usernames and, for usernames, a second Noul for phonetic or look-alike disguises. The threshold and max policy live in Worker code, with OpenAPI docs generated via chanfana and Hono.
Jev Integrations & Adapters#community#cloudflare-workers#moderation
Community
4rays/profanity-checkerTypeScript
4rays/profanity-checkerTypeScriptThird-party TypeScript check that compares Jev (typesafe-ai/jev) against openai/gpt-4o-mini and anthropic/claude-sonnet-4.5 under identical conditions, routing 60 synthetic booking inquiries in four languages for a photo-shoot service, all through one Vercel AI Gateway key.
Jev Benchmarks & Evaluations#community#benchmark#comparison
Community
Shogo-nfrealmusic/jev-evalTypeScript
Shogo-nfrealmusic/jev-evalTypeScriptPre-registered benchmark adding Jev 1.13 to Stanford MedHELM's MedHallu results: one Noul asks whether a proposed answer misrepresents its PubMed abstract. Jev scored 92.9% on 1,000 test items at a 204 ms median and USD 0.03 per 1,000 checks through OpenRouter.
Jev Benchmarks & Evaluations#community#medical#hallucination
Community
stperic/jev-medhallu-benchmarkPython
stperic/jev-medhallu-benchmarkPythonTerminal agent for Polymarket's BTC Up or Down five-minute markets. Roughly every five seconds it asks Jev whether BTC finishes UP or DOWN versus the window open, then abstains or buys once and holds to resolution. Defaults to dry-run; live orders are opt-in.
Jev Tools & CLIs#community#trading#prediction-markets
Ascend NPU fork of the Laya decision checkpoints that answers Jev-style Choice, Score and Noul questions in a single forward pass on Huawei 910B hardware. It reports 37-47 ms median for a four-question request, 33.8x-70.9x faster than one container CPU thread.
Jev Models & Reimplementations#community#ascend-npu#decision-model
Community
zzhdbw/laya-AscendPython
zzhdbw/laya-AscendPythonPython multi-agent runtime that ships Jev natively in an optional extras install: agents ask typed Choice, Score and Noul questions through a shared decision client, the Kernel can pick specialist subagents by Choice, and RAG passages with a prompt-injection Noul above 0.70 are withheld.
Jev Integrations & Adapters#community#framework#mesh
Serves DiffusionGemma-Jev behind a TypeSafe-compatible API on Google Cloud Run with an NVIDIA RTX PRO 6000 GPU, built on mmastrac/djev. Cold start is about 47.5 s and the median server response 61 ms; it exposes /v1/systemone plus snake, dino and tetris demos.
Jev Models & Reimplementations#community#cloud-run#gpu
Community
taeold/djev-runHTML
taeold/djev-runHTMLRust agent workbench for ongoing work that keeps branch decisions in their own crate and backend notes in the adapter. Its first decision backend is Cloudflare's Clef, borrowing Clef's System One-shaped state and questions request instead of reinventing the interface.
Jev Integrations & Adapters#community#agent-runtime#rust
Community
holon-run/holonRust
holon-run/holonRustMeasured robotics study that runs Jev as the decision layer for a 10,000-robot warehouse fleet over 41 bilingual incident templates and publishes a crossover against a self-hosted ModernBERT: 0.527 s p50, $24.57 per million decisions, and 91.3% agreement with template labels.
Jev Benchmarks & Evaluations#community#robotics#fleet-triage
Community
robokrunch/jev-physical-aiPython
robokrunch/jev-physical-aiPythonReal-time geopolitical intelligence dashboard that uses TypeSafe Jev questions to score news headline severity into five threat levels and categorize events across 14 conflict, cyber and infrastructure domains, alongside news aggregation and a Country Instability Index.
Jev Integrations & Adapters#community#osint#geopolitics
Community
koala73/worldmonitorTypeScript
koala73/worldmonitorTypeScriptOpen-source link attribution platform that calls typesafe-ai/jev in malicious-link-check.ts before a short link is created, so the URL is gated by a typed Jev verdict rather than a static blocklist. Next.js and TypeScript with an open-core license.
Jev Integrations & Adapters#community#link-shortener#attribution
Community
dubinc/dubTypeScript
dubinc/dubTypeScriptOpenClaw plugin that checks every outgoing agent message against its destination channel tier, running local key-format and term rules and then five Jev Noul questions in one call through OpenClaw's decisionModel, which can point at hosted Jev or a local Kev.
Jev Tools & CLIs#community#openclaw#guardrails
Focus mode for Omarchy and Hyprland that judges each screen against the task you declared and escalates from a red reticle to a window haze and, as a last resort, closing the drifting browser tab. Each check is one Jev on-task classification, with screenshots OCR'd locally and never uploaded.
Jev Integrations & Adapters#community#focus#linux
Community
iYassr/omarchy-laserPython
iYassr/omarchy-laserPythonA Jev-style typed-decision baseline built on the frozen Qwen3.5-4B checkpoint that accepts a local image path directly, letting the vision-language model score declared options without generating text. Ships scoring modes, a WebGPU browser demo and benchmark results measured on an RTX 3090.
Jev Models & Reimplementations#community#multimodal#open-models
Community
jiangxiluning/Visual-JevPython
jiangxiluning/Visual-JevPythonApache-2.0 decision models for browser agents: a Qwen3.5-35B-A3B fine-tune that answers jev-ultrafast's per-step operation and target-element Choice questions in one forward pass behind a Jev-compatible /v1/systemone API. Includes training code, a serving stack and a 125-task real-website evaluation.
Jev Models & Reimplementations#community#browser#open-weights
Community
lexmount/WebJevPython
lexmount/WebJevPythonA chatbot with no language model: every word is picked from roughly 4,700 options by Jev Choice questions, with confidence-driven lookahead, beam search across sentence directions and a self-critique loop that rewrites weak sentences. Code for the paper and the live demo at talktojev.com.
Jev Demos & Experiments#community#chatbot#research
Community
xucian/talktojevPython
xucian/talktojevPythonAn Apache-2.0 0.8B decision model that returns calibrated probabilities for yes/no, choice and score questions on CPU. Distributed as GGUF for llama.cpp and served behind a Jev-style /v1/systemone API, so existing Jev clients mostly need only a new base URL.
Jev Models & Reimplementations#community#gguf#local-inference
Community
kouhxp/gutsyHTML
kouhxp/gutsyHTMLStart here with the Jev AI model
Hand-picked entries the maintainers recommend first, from official primitives to community tools.
The Jev Day release post: Jev 1.14.0 under jev-preview plus three danger-zone features — composable images on both models, the box question type on 1.14 only, and opt-in 262k context.
Jev Guides & ArticlesArticle#official#release#vision
Official
The box question type: one bounding box per question, returned as four edges that are fractions of the image, plus confidence, with no criteria field and no not-found value.
Jev Practices & PatternsDocs#official#docs#vision
Official
LiteLLM's Day 0 post for TypeSafe Jev 1.14: the proxy adds box questions, image input and long-context mode on both POST /v1/systemone and POST /v1/decisions, forwarding TypeSafe-Danger-Zone headers only to TypeSafe deployments.
Jev Integrations & AdaptersArticle#community#litellm#gateway
Community
Newest Jev AI model resources
The latest additions to the directory, newest first.
Do Multimodal Models Decide Consistently on Equivalent Optical Spectra?Jev Benchmarks & Evaluations
@harlan-zw/jevJev Repos & SDKs
Jev-AD: Safe Language-Guided Autonomous Driving via a Language World ModelJev Demos & Experiments
Jev GUI Training PreviewJev Models & Reimplementations
- jev-playgroundJev Demos & Experiments
- JeviewJev Tools & CLIs
From the Jev community
Watch walkthroughs, read the threads, and see what builders are posting.
YouTube: KodeKloud's three-minute primer: what a System One model decides, and why it answers in milliseconds.
YouTube: Caleb Writes Code explains what Jev is and how to call it, in seven minutes.
YouTube: Greg Isenberg and Ryan Vogel on the businesses Jev unlocks, and a path in through the Vercel AI Gateway.
YouTube: CJ from Syntax demos browser use, classification, code review, a model router, and a chat bot with no LLM.
YouTube: Ryan Vogel runs Jev on 100 and then 1,000 emails: category, priority, spam, and reply predictions.
YouTube: AICodeKing tests support routing, refund detection, prompt-injection resistance, and browser automation.
Hacker News: Show HN: Ad Spend Guard gates budget before the auction, not the creative after.
Show HN: Gating ad budget with a decision modelRead the thread on Hacker NewsReddit: Reranking rebooking options with a decision model, ranked with reasons.
Hacker News: Pick Verify: a single decision at the warehouse pick station catches confusable picks.
Show HN: Verifying robot picks with a decision modelRead the thread on Hacker NewsHacker News: Decision Index 0.2.1 scores open reproductions of Jev on a frozen suite.
jackbravo4 pointsDecision Index 0.2.1 – 70 open reproductions of TypeSafe Jev's Decision ModelRead the thread on Hacker NewsHacker News: Software Bombe and live Enigma demo where Jev ranks cribs and judges plaintext.
ag_212 pointsShow HN: Jev as the Bletchley Park Analyst: A Software Bombe on EnigmaRead the thread on Hacker NewsHacker News: Show HN for the decide CLI: brew install, file context, and multi-question shell scripts.
vsekhar2 pointsShow HN: Decide – Jev decisions in the shell, scripts, and agent skillsRead the thread on Hacker NewsHow entries are chosen
Every entry is reviewed against the same bar, whether it comes from TypeSafe or the community.
- Public and working — no paywalls, sign-up walls, or dead links.
- Concrete — it has to be about Jev and the System One API, not generic LLM content.
- Useful today — something a developer can learn from or use right now.
- Distinct — if a similar entry exists, the description has to say what makes this one different: a different runtime, a cheaper path, a measured result, or a narrower focus.
- Documented — repos state their license, and docs are in English or carry an English summary.
Spam, affiliate links, and thin AI-generated content are rejected. New entries are expected to ship with a deep dive: two to five highlights, caveats, a quickstart snippet where one helps, and a verification date. Star counts are refreshed when an entry is touched.
Common questions
Short answers about Jev and how this directory works.
What is the Jev AI model?
Jev is TypeSafe AI's first System One model — an AI model that takes a state plus typed questions and returns one structured answer per question: a choice, an ordered score, or the probability of yes, with calibrated confidence on Choice and Score answers. Code can branch on the result without parsing generated text.
What is the difference between Choice, Score, and Noul?
They are the three question primitives. Choice picks one of up to 255 options, Score rates on 2 to 10 ordered levels, and Noul answers yes or no. Choice and Score answers carry a confidence between 0 and 1; a Noul answer is the probability of yes.
Which Jev SDKs and client libraries are available?
TypeSafe maintains official JavaScript/TypeScript and Python SDKs plus a Python adapter. The community has built clients for Go, .NET, PHP, Laravel, Rust, Elixir, Ruby, and Scala, along with framework integrations such as DSPy, LlamaIndex, and Home Assistant. All of them are listed in the Repos & SDKs category.
Is the directory free, and is it affiliated with TypeSafe AI?
The directory is free to browse: every entry is reviewed, and spam, affiliate links, and sign-up walls are rejected. JevDirectory.org is community-run and not affiliated with TypeSafe AI — Jev and System One are TypeSafe AI trademarks.
How often is the directory updated?
Entries are added as new resources appear and re-checked when they are touched. The directory currently holds 3919 entries from 293 source sites, last updated Nov 6, 2026.
What is a verified deep dive?
Most entries include a deep dive: two to five highlight bullets someone would only know from using the resource, a caveats note about limits and requirements, an optional quickstart snippet, and the date the link was last checked. 3919 of the 3919 entries carry one today.
For the canonical details, read the official TypeSafe docs and the API reference.