What is Jev? TypeSafe's decision model, on OpenRouter

What people are building

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  Instant compaction: score the tool calls, drop what does not matter

  Compaction turned into a scoring problem: grade every tool call, drop the ones the model judges irrelevant, and skip the summarisation pass entirely. The most-liked post we have catalogued, and the idea that two later posts in this same column argue with.

  10,846 likes2026-09-17

• Repository
  Repository

  browser-use/jev-ultrafast

  The browser agent we read line by line for the resources column: Jev picks the next action from an indexed space instead of emitting free-form clicks. The most-starred build in this list, and the one with the clearest engineering write-up.

  20,611 starsPython

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  Jev is HERE. How to use it

  The most-watched walkthrough we found: twenty-eight minutes, published three days after launch. Watch this one if you want to see the thing being set up and run rather than explained.

  518,230 viewsGreg Isenberg

• Hacker News · source

  Introducing System One Models and Jev

  The launch thread, and the largest single discussion of this model we can count. Start here for volume and for the objections raised in week one; the vendor's own announcement is in the resources column.

  1,949 points2026-09-15

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  The designer's demo that reached the design crowd

  A designer's demo, and the most-liked post in this batch: the audience is design people, not AI people, which is worth noticing about who the model reached. The clip is the content; there is no benchmark in it.

  10,238 likes2026-09-19

• Repository
  Repository

  OpenByteInc/QuantDinger

  An open-source trading OS. It is here because its own description puts the decision loop at the centre rather than a chat window; the strategy numbers are the author's, and we have not audited them.

  12,211 starsPython

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  Video · source

  Jev explained in 7min..

  The short version, and the one to start with if you are still deciding whether this is a category or a product. Seven minutes and no setup.

  426,311 viewsCaleb Writes Code

• Hacker News · source

  Jev in 25 Lines of Python

  The most-read thread of the week, and it is a parody: a local Qwen model reproducing Jev's visible behaviour in twenty-five lines of Python. The discussion is better than the joke — the top comment asks for the latency and compute comparison the parody leaves out, which is exactly the measurement Jev's own case rests on.

  666 points2026-09-23

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  Browser Use + Jev searched a flight in seven seconds

  The most-liked post in the whole list, and the one behind the browser-use repository we already cover: a flight search in seven seconds for under half a cent. Author's numbers.

  9,093 likes2026-09-17

• Repository
  Repository

  YaoApp/yao

  A self-hosted agent workspace with eight thousand stars that added Jev as one of its decision models, announced in the README rather than in a launch post. Useful as evidence of the pattern reaching infrastructure other people already run.

  8,028 starsGo

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  JEV Breakdown: The First AI Model Built For Code

  A breakdown framed around code instead of chat, which is the framing that matches what the model actually does. The claim in the title is the video's, not ours.

  377,836 viewsRob Shocks

• Hacker News · source

  Ollaya – Ollama for open-source, Jev-style decision models

  The week's largest discussion of the decision-model stack: an Ollama-style daemon for open decision models behind TypeSafe's wire format. 587 points and 29 comments when we read it, and the argument in the comments is about whether a registry is the missing piece or another layer nobody needs.

  587 points2026-09-25

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  A Claude plugin that trims tool results with Jev

  The most-liked post here: Jev working as a plugin inside Claude, for review work. The interesting part is the shape rather than the excitement — a large model writes, Jev decides.

  8,406 likes2026-09-18

• Repository
  Repository

  jaredpalmer/kev

  The Kev family: the same decide-and-act shape rebuilt on Qwen3.5 instead of the hosted API. It is also the build whose Hacker News thread trended, and the clearest sign that the pattern travels between models.

  7,262 starsPython

• Video
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  Jev is incredible

  Half an hour of enthusiasm rather than instruction, useful as a temperature reading of how the launch landed with developers who build for a living.

  375,466 viewsTheo - t3․gg

• Hacker News · source

  Jeff – Jev-compatible 0.8B decision models, trained at home, ~30 ms

  An 0.8B Jev-compatible decision model family you can train at home, shipped with GGUF builds, adapters and a hosted playground at jeffhub.ai. It is the most-discussed item in this column — 231 comments — and most of that argument is about whether a model this small holds up on real classification.

  576 points2026-09-28

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  An agent beat the Ender Dragon in 8 minutes 43 seconds

  An agent loop playing Minecraft end to end, with the decision model choosing each move and a language model out of the loop. A game is the cheapest place to watch that loop fail: every wrong call is visible within a second.

  7,948 likes2026-09-20

• Repository
  Repository

  tamaratran/fast-jev-compaction

  A Claude Code plugin that replaces the compaction step with a Jev call. Small, unglamorous, and among the highest-starred entries here — the pattern tends to show up in tooling before it shows up in products.

  6,978 starsTypeScript

• Video
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  Jev - The Ultimate Classification Model?

  Reads Jev as a classifier, which is the closest everyday description of a typed-decision model. Worth watching for that framing alone.

  323,066 viewsSam Witteveen

• Hacker News · source

  Kev: Tiny Jev-like family of decision models built on top of Qwen3.5

  A third-party rebuild of the same idea on Qwen3.5 instead of a call to the hosted model. The clearest evidence that what people are copying is the decide-act loop, not the endpoint.

  429 points2026-09-21

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  Jev does not replace GPT or Claude

  The most-liked explanation in this list, and the only one whose opening move is to say what Jev does not replace. Start here if the rest of the column reads as enthusiasm.

  7,533 likes2026-09-16

• Repository
  Repository

  jev-chat/jev-chat-jarvis

  A phone-resident assistant that reads chat threads and proposes replies. The description is the author's and is written in Chinese; we have not run it, so nothing here is a claim about how well it works.

  6,698 starsKotlin

• Video
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  Jev: System One Model

  An explainer for the question everybody asks first — why is this model interesting when it cannot write — and it answers it with the mechanism rather than the marketing. Two hundred and fifty thousand views, which makes it the video most readers will meet this model through.

  258,386 viewsZAUEY (Claire Zau)

• Hacker News · source

  OpenAI is well positioned to fast-follow Jev

  A 323-point argument that OpenAI is well positioned to fast-follow this shape of model, from a blog that writes about model economics. Whether or not the prediction lands, the thread is the clearest statement of the strategic question the launch raised.

  323 points2026-09-22

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  724 competitor ads broken down in forty seconds

  Seven hundred competitor ads broken down in forty seconds — every hook and format classified, one decision per ad. This is the largest corpus in the column so far and the clearest case for the model as a labelling engine.

  6,819 likes2026-09-17

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  Repository

  TheoLeeCJ/SemIf

  Semantic conditionals, run on open models on a single 3090. This is the closest thing in the list to a drop-in replacement for an if-statement, which is the plainest statement of what the idea is for.

  4,405 starsPython

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  Jev Explained: Demos and Use Cases

  Demo-heavy and grounded in concrete uses rather than architecture, which makes it the better second watch after the walkthrough above.

  217,129 viewsSyntax

• Hacker News · source

  Show HN: Jev Plays Pokémon Red

  A Show HN that answers the first question anybody asks about a model this fast: can it play something harder than Tetris? Pokémon Red, open-sourced, with the author's own caveat that Jev is not yet fast enough for Doom. The comments are mostly about frame budgets and where the loop breaks.

  262 points2026-09-25

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  A third party's own System One family (not Jev)

  Not built with Jev: this is a third party announcing its own family of System One models, which is the clearest sign that the category now exists outside the company that named it. Kept in the column because the comparison is the news.

  5,506 likes2026-09-18

• Repository
  Repository

  zilliztech/memsearch

  The largest company-backed project in this batch: a semantic memory layer for coding agents from the team behind Milvus, with Jev as an opt-in reranker. Worth a row because the integration is one bullet in a long feature list, which is how adoption looks when it stops being news.

  2,662 starsPython

• Video
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  Why I couldn't build Jev at OpenAI — Diogo Almeida, TypeSafe Co-founder & CEO

  The founder's own account of why the model could not have been built at OpenAI: years spent on instruction following, and the conclusion that a bounded decision is a different problem from a generated answer. Long, first-person, and the only row in this column that is the company talking about itself at length.

  203,701 viewsLatent Space

• Hacker News · source

  Jeeves. Reasoning improves Jev-like decision models

  PostHog's reasoning Jev-style classifier: a 9B model with a diffusion drafter, trained with SFT and CISPO, MIT-licensed with weights on Hugging Face. Its title carries the claim worth testing — that adding reasoning improves a decision model, which runs against the argument that speed is the whole point.

  242 points2026-09-29

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  Jev clearly explained: what it is and what it is not

  The most-liked thing we have read from the second wave — over five thousand likes — and it is an explainer rather than a benchmark: why using a language model for a bounded decision is a hammer, and what the alternative looks like when you only need a choice.

  5,424 likes2026-09-18

• Repository
  Repository

  jarrodwatts/jev-trader

  One trade decision per Monad block, made by Jev — the most literal reading of the model in this list, a decision every few hundred milliseconds with real money behind it.

  2,518 starsTypeScript

• Video
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  Building a Harness with Jev

  A harness build rather than a model review: how to put the decision call inside an agent loop, what to send it, and what to do with an answer that arrives as a probability. Two hundred thousand views, and the most practical of the three.

  202,062 viewsLangChain

• Hacker News · source

  Jev-Leftpad

  The joke build: the decision pattern wrapped around a trivial utility. Worth reading as a size reference for how little code the smallest useful instance needs.

  229 points2026-09-21

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  A bot that decides every 300 ms block and trades on an on-chain book

  A bot that asks Jev whether to buy or sell from a price feed and places the order on an on-chain order book every three-hundred-millisecond block. Real money on a real venue is the claim, and it is one we have not checked against the chain.

  5,132 likes2026-09-16

• Repository

  dzhng/jevgrep

  A CLI that finds code by asking what it does, built for coding agents: Jev picks the files and the source context worth reading instead of the agent grepping its way in. The README's headline is a cost claim — "Same intelligence. About 30% lower cost." — measured on their own ten-task SWE benchmark.

  2,479 stars—

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  JEV: How It Works and What You Can Build

  The only walkthrough in this column that publishes its own chapter list, and the order is the one we would suggest: routing at 2:08, then what Jev is, then the three answer types, and cost and speed only after that. Twenty minutes, and the first four are the part a developer needs.

  152,475 viewsRiley Brown

• Hacker News · source

  I turned Jev into a (lousy) chatbot

  Someone aimed a decision model at a job that belongs to a language model and said so in the title. The thread is the argument about where that line actually falls.

  170 points2026-09-20

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  Doom at ten decisions a second, about seven dollars an hour

  Doom played at roughly ten decisions a second, which the vendor works out to about seven dollars an hour of model calls. The cost of a continuous loop is the number this column keeps needing, and here the company that sells it put the arithmetic in public.

  5,051 likes2026-09-15

• Repository
  Repository

  TianyuCodings/NanoJev

  A small replica of the mechanics: parallel decisions, dynamic routing. Useful as the readable version of the architecture if you are not going to work through the paper.

  2,317 starsPython

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  Jev by TypeSafe AI | What is a System-1 Decision Model | CampusX

  A 90-minute session that treats Jev as a teaching subject rather than news: what a System One model is, why giving up token generation changes what a model can be used for, and where it sits in a pipeline. The longest explainer we track, and the one that assumes no background.

  150,593 viewsCampusX

• Hacker News · source

  Reverse-engineered Jev-like model

  An independent reconstruction of the architecture. Read it next to the vendor's quickstart, because the two disagree in places worth knowing about.

  167 points2026-09-16

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  Tesla's driving agent rebuilt in an afternoon

  A driving-simulation agent rebuilt in an afternoon, with the decision model steering. 'Under an hour' is a claim about the integration rather than the task, and the author is explicit that it took one sitting.

  4,859 likes2026-09-16

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  Repository

  szczyglis-dev/py-gpt

  Not a Jev project: a large multi-provider desktop assistant that added a Jev / System One (inline) plugin for classification, routing, selection, verification and scoring. It is the shape adoption takes once a model stops being news — one entry in a plugin list, and the repo carries a jev topic tag.

  1,951 starsPython

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  Open Jev Models Are Here!!

  Runs seven open Jev-style models against a public benchmark rather than explaining the API again, which makes it the most useful of the second wave. Sponsored by Dell for the compute and the sponsorship is stated in the description; the models named there are the ones we list in the builds column.

  142,755 viewsSam Witteveen

• Hacker News · source

  Decision models like Jev don't beat LLM-as-a-judge or traditional classifiers

  Red Hat's AI Safety team benchmarked nine guardrail candidates across four methodologies — CPU-scale pre-trained classifiers, LLM-as-a-judge and decision models — to ask whether Jev-style models earn their place for risk detection. It is the first enterprise-scale comparison we have seen on this question, and its answer leans toward the cheap old thing rather than either vendor's story.

  166 points2026-10-02

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  The coolest Jev projects on X, in one thread

  A curated thread of Jev projects from X: the same instinct as this column, by somebody reading the same timeline. Overlaps our builds list and belongs beside it.

  4,449 likes2026-09-18

• Repository

  realZachi/pg-jev

  A PostgreSQL extension that answers plain-language questions about your tables: Jev does the choosing, the database does the work. It puts the decision model inside the database rather than beside it, which is the same architectural bet Cloudflare made by putting Jev behind env.AI.run.

  1,068 stars—

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  Will Jev Replace LLM's? What is Jev From TypeSafe AI

  Framed as a question — will Jev replace LLMs — which is the debate rather than the specification. Worth knowing that the description spends more of its lines on the channel's bootcamp than on the model; if you want the answer types, the shorter explainers in this column get there faster.

  130,120 viewsKrish Naik

• Hacker News · source

  Show HN: JevBench, a reproducible benchmark for typed decision models

  The Hacker News thread for JevBench, the community benchmark that made comparison between these models possible. The most interesting comment quotes the vendor's own reasoning for not publishing benchmarks — which is a fair thing to have next to a benchmark somebody else wrote.

  145 points2026-09-22

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  Real-time virtual try-on for a fashion haul

  Real-time virtual try-on for a fashion haul: a decision per frame rather than per document, which is the latency end of what these models are for. The demo is a studio experiment, not a product, and the author says so.

  4,339 likes2026-09-19

• Repository

  wy-coliney/jev-browser-use

  A browser skill that splits the loop in two: Jev owns clicking, toggling, scrolling and navigation, while Codex keeps text input, visual judgment and the final verification. The README claims 5–10x faster browser operations in the author's own product workflows at EZCollegeApp.

  1,021 stars—

• Video
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  What is Jev and How to Use it?

  A twenty-two minute explainer whose chapter list is a syllabus: what Jev is, how it differs, speed and price, then state, questions and answers, the three answer types, the playground, and finally requests. It is the one to send somebody who has never heard of a System One model.

  123,925 viewsCodevolution

• Hacker News · source

  A single function Jev-like wrapper for LLMs, including vision models

  A short argument with code: wrap any LLM — vision models included — in a single function that returns a decision rather than text. 135 points and 12 comments, and a useful counterweight to the framework-shaped projects in the builds column, because it shows how little scaffolding the idea actually needs.

  135 points2026-09-26

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  500 emails classified in seconds for a few cents

  Five hundred emails classified in seconds for a few cents, which is the claim; the number is the author's and we have not run it. The interesting part is the shape — bulk triage where per-item cost decides whether it is viable at all.

  3,879 likes2026-09-17

• Repository
  Repository

  awlevin/typesafe-computer-use

  Computer use for about $0.0002 a step, on macOS: OCR the screen, classify the next action with TypeSafe, click. Python 3.12 with an MIT licence and a CI badge, and the price per step is in the repository description rather than buried in a table. We have not run it.

  1,012 starsPython

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  Video · source

  Jev de TypeSafe AI: el modelo que NO escribe texto

  In Spanish, thirty-one minutes, and it explains the category before the API: what a System One model is and why the decision stays in your code. Worth listing for the half of the audience that does not read English explainers — the framing is the same, the language is not.

  98,731 viewsFazt

• Hacker News · source

  Open-sourced jev architecture last year with model,paper and dataset

  A prior publication arguing the pattern predates this release, with the paper and dataset linked in the thread. Useful as the before-picture when the naming conversation comes up.

  96 points2026-09-17

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  Jev is on OpenRouter, in beta

  OpenRouter's own announcement of the beta listing — the post that made the model reachable without a waitlist, and the reason the listing page this site links to exists at all.

  3,877 likes2026-09-18

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  Repository

  reticlehq/reticle

  File this one under roadmap, which is where Reticle puts Jev: the README says plainly that nothing ships against it yet. The case is still worth reading, because it is the only project here that names the decisions it would route — is this page settled, is this finding worth chasing — and then says why a 70–500ms typed answer beats an LLM there.

  895 starsTypeScript

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  Jev - La nuova era dell’ai è arrivata (e non genera testo)

  The longest of the explainers at forty-two minutes, in Italian, and the only one that opens by arguing about the category rather than the model: not an LLM, not a chatbot, a system built to return decisions. Its own framing, not ours.

  86,795 viewsSimone Rizzo

• Hacker News · source

  Jev – A curation of Jev demos on X, tools, skills, and integrations

  A curation of demos, tools and integrations, submitted as a repository and argued about in the comments. Our own X column is the same idea with a person reading each row first; this is the version that scales by not reading them, and the comments show where that shows.

  93 points2026-09-22

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  1,500 of one person's own emails, classified

  One person running fifteen hundred of his own emails through the model and reporting that it works well. A personal inbox is a fair place to start and also the reason the post carries no accuracy figure: the only labels in it are his own.

  3,551 likes2026-09-16

• Repository
  Repository

  nokia-applied-research/AnyJev

  A research lab's answer to the question this whole column circles: can an ordinary open LLM produce typed decisions without generating tokens? Nokia's team ships calibration heads for five Qwen3 sizes and reports order-flip falling from 0.230 to 0.073 and calibration error from 0.240 to 0.095 with no labels. The numbers are theirs, on their dataset.

  801 starsPython

• Hacker News · source

  Jev Ultrafast: A browser agent with a dynamic, indexed action space

  A browser agent driving an indexed action space. We read this repository line by line for the resources column; the thread is where its author answers questions about it.

  91 points2026-09-17

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  Seven hundred outreach messages scored in forty seconds

  Seven hundred leads and the outreach message written for each one, scored in forty seconds for nine cents, with mismatches between message and lead flagged. Judging a written sentence against an intent is the errand; the accuracy claim is the author's and there is no holdout in the post.

  3,413 likes2026-09-18

• Repository
  Repository

  kitfunso/hippo-memory

  The most carefully reported Jev result in this list, including its own negative: an opt-in reranker takes R@1 from 0.41 to 0.62 on a private 300-query store at about $0.0004 a recall, the margin held in 20 of 20 seeds — and three graded tests still did not beat the free local cross-encoder. Off by default.

  761 starsTypeScript

• Hacker News · source

  Show HN: CUA-S1 – A System One Model for Computer Use

  A separate System One model, aimed at computer use rather than typed decisions. The clearest sign that the name is turning into a category rather than a product.

  90 points2026-09-19

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  Jev as an “Internet moment” for the AI industry

  The strongest version of the hype, posted as text. Read it for how the analogy is argued; the post itself offers no number, and none of the claims in it are ours.

  3,348 likes2026-09-18

• Repository
  Repository

  wfzyx/von

  The open substitute, published with its own comparison against the model it substitutes: 72.0% macro on a 49-task suite against TypeSafe's 96.6%, and 9.00 kills against 5.62 in ViZDoom — a clear loss on accuracy and a win on the real-time loop. Its GitHub description says sub-15ms and its README headline says sub-25ms; both numbers are the publisher's.

  716 starsPython

• Hacker News · source

  Turning GLM-5.3-Flash into a Jev-like decision model

  PrivateMode's write-up of getting Jev-like behaviour out of a standard open model by crafting the prompt so the first output token is the answer: one forward pass, then a benchmark against both Jev and Laya. One of very few head-to-head measurements in this column that was not produced by a vendor.

  72 points2026-09-26

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  Years of bookmarks, run through Jev

  The joke that travelled furthest in this batch: years of bookmarked posts as a workload for a fast decision model. The demo is the point.

  3,153 likes2026-09-20

• Repository
  Repository

  anishfn/shapeshift

  The clearest design pattern in the batch, and the author states it in one line: Jev decides, code computes. Fourteen typed questions in a single call decide what the text box should become, while dates, amounts and units are parsed by deterministic code.

  687 starsTypeScript

• Hacker News · source

  Jev Can't Be Calibrated

  The sceptic's post, and the most valuable one in this topic's discussion: four hundred rolls of a fair die, and the model's probabilities never moved off the first face. It is a one-experiment argument, so read it as a sharp case rather than a verdict — and note that it lands on the same failure the model's own card warns about.

  62 points2026-09-23

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  A full Jev tutorial: what it is and what to build

  The fullest tutorial in this batch — what it is, how to build with it, what it unlocks. Long, and the nearest thing to the official walkthrough that was never published.

  3,148 likes2026-09-17

• Repository
  Repository

  Rizzo-AI-Academy/rizzo-flow

  A local-first implementation of the same interface: unstructured state in, typed decisions with probabilities out, no tokens generated, and an HTTP surface written to match TypeSafe's so an existing client can be repointed at your own machine. The README is explicit that it implements the idea rather than reproducing the weights.

  626 starsPython

• Hacker News · source

  What Is RLCD? The Secret Behind Jev

  An explainer for the training method behind this class of model, with the objection attached: the top comment points out that the piece never defines the acronym in its own title. Useful as a pointer to the technique, not as the reference for it.

  60 points2026-09-24

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  LLMs vs Jev: the difference is not what you think

  A widely shared explainer whose first move is to say the key difference is not speed. Short, and the numbers inside it are the vendor's, as they are everywhere else in this column.

  3,001 likes2026-09-19

• Repository
  Repository

  devagrawal09/jev-review

  Read the README for the pipeline rather than the dashboard: a Null risk matrix, then Choice and Score file profiles, evidence selection, mechanism classification, severity, and a conditional Choice that routes which reviewer sees it. Orchestration stays in code and Jev only answers the bounded judgements — which is the pattern to copy.

  625 starsTypeScript

• Hacker News · source

  How accurately calibrated is Jev?

  A measured attack on the calibration claim, with the whole experiment series run for under $4. The author's description of the architecture — a pre-trained transformer with a classifier bolted on the end — is the clearest short explanation of what Jev is that we have read from outside TypeSafe, whether or not the conclusion holds.

  55 points2026-10-02

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  LangChain benchmarked Jev against LLM judges

  The most consequential post in this batch, and not because of the numbers: a framework company ran the comparison everyone else has been arguing about from intuitions. They tested Jev against LLM judges on accuracy, repeatability, latency and cost, and published the method rather than the conclusion.

  2,994 likes2026-09-19

• Repository
  Repository

  Sac-Y/Jev-cu

  The one repository in this queue with no published description, and the one that states its design constraint most plainly: text goes in and screenshots do not, a local policy gate blocks the sensitive actions, and Codex does the reading and clicking. The README is in Chinese.

  606 starsJavaScript

• Hacker News · source

  Jev introduces a new shape of LLM

  Simon Willison's note on the launch, and the thread underneath is about what a closed decision model means for bias and audit: a probability you cannot interrogate is still a judgement. Worth reading for the questions rather than the answers.

  52 points2026-09-22

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  Super Mario Bros played by the decision model

  Super Mario Bros played by the model, which is the earliest demo in this batch and the one that convinced a lot of people the latency claim was real. A game loop is the honest test of whether the round trip fits.

  2,910 likes2026-09-16

• Repository
  Repository

  jev-chat/jev-chat-windows

  The Windows build of the chat assistant that reads a conversation off the screen with local OCR, asks Jev what the other person means, and offers three replies. The decision kernel is shared with the Android version already on this wall, which is why this row is short.

  599 starsPython

• Hacker News · source

  Jev-Driven SRE Diagnosis: What Worked and What Failed

  A research group handed Jev a view of a cluster and let its fast judgments choose where to investigate and which evidence supported a diagnosis, then published all 105 diagnoses including the ones that went wrong. Negative results with the failure cases printed are rare in this topic, and worth more than another demo.

  50 points2026-10-07

Every entry on this page is in one of the columns, with the full list and its filters: Built with Jev (28) · Seen on X (101) · Videos (16) · Threads and write-ups (64)

The 10 use cases cover 180 of the 209 records in this topic; the rest are announcements and explainers, so they are in no use case and in no chip. A chip's number counts every record in the topic — the wall on this page is a sample of it, so switching a chip on shows the matching cards from these 88, and the complete list behind each use case is its own page, linked from Use cases.