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ANNOUNCING: Open Jev Playground Try all the open-source alternatives to Jev as APIs > 50% cheaper than Jev 🤯 > $0.021 per 1M tokens > Hosted as OpenAI-compatible endpoints Explore the playground ↓

Eli Mernit

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16,691 görüntüleme • 1 ay önce •via X (Twitter)

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Why is nobody posting about this? This is hands down the BEST way to run Jev right now. You can use the new Jev Playground to start running decisions with Jev for FREE. You're welcome. →

Why is nobody posting about this? This is hands down the BEST way to run Jev right now. You can use the new Jev Playground to start running decisions with Jev for FREE. You're welcome. →

Miles Deutscher

37,131 görüntüleme • 1 ay önce

Introducing Amos 1, four open-weight decision models from 0.5B to 27B. > 94.9% on Decision Bench, ahead of Perplexity, Gemini and Jev > beats Jev by 10 points on JevBench hard > reads photos and answers with boxes > decisions in 27 to 122 ms, free API, Apache 2.0

Introducing Amos 1, four open-weight decision models from 0.5B to 27B. > 94.9% on Decision Bench, ahead of Perplexity, Gemini and Jev > beats Jev by 10 points on JevBench hard > reads photos and answers with boxes > decisions in 27 to 122 ms, free API, Apache 2.0

Zaid

35,135 görüntüleme • 20 gün önce

I built a thing using Jev. Have you ever been annoyed by not finding an old Claude Code or Codex chat? => Now you can just describe what it was about and Jev finds it in milliseconds. Open Source:

I built a thing using Jev. Have you ever been annoyed by not finding an old Claude Code or Codex chat? => Now you can just describe what it was about and Jev finds it in milliseconds. Open Source:

Florian S

85,808 görüntüleme • 1 ay önce

Now make it actually follow them use Jev to enforce the rules linters cannot catch open-source:

Now make it actually follow them use Jev to enforce the rules linters cannot catch open-source:

Ohans Emmanuel

13,472 görüntüleme • 1 ay önce

🆓 Free Open-Source Jev 🤝 LangSmith Gateway Decision models are becoming a first-class part of the LangSmith Gateway! We're serving SemIf, an open-source decision model, free for the next week. Compatible with the TypeSafe SDK - just change a string to try it! Docs in 🧵

🆓 Free Open-Source Jev 🤝 LangSmith Gateway Decision models are becoming a first-class part of the LangSmith Gateway! We're serving SemIf, an open-source decision model, free for the next week. Compatible with the TypeSafe SDK - just change a string to try it! Docs in 🧵

Jacob Lee

40,499 görüntüleme • 1 ay önce

computer use with openai's decisions api might be the next big thing. i built arc-cua - a fast computer use layer powered by decision models. >no screenshot + LLM call after each action. >supports jev & decisions api. open source. link below.

computer use with openai's decisions api might be the next big thing. i built arc-cua - a fast computer use layer powered by decision models. >no screenshot + LLM call after each action. >supports jev & decisions api. open source. link below.

shiv

15,904 görüntüleme • 25 gün önce

Built a tax document classifier with Jev. We ingest thousands of tax documents using an LLM pipeline I built last tax season. I read multiple articles as late as April this year claiming AI fails at tax document classification. Wasn't the case back then, and it's proved wrong again now. Jev classifies 100% of our tax document corpus at $0.001 per page. 34x cheaper and 6x faster than the LLM setup. Open sourcing it:

Built a tax document classifier with Jev. We ingest thousands of tax documents using an LLM pipeline I built last tax season. I read multiple articles as late as April this year claiming AI fails at tax document classification. Wasn't the case back then, and it's proved wrong again now. Jev classifies 100% of our tax document corpus at $0.001 per page. 34x cheaper and 6x faster than the LLM setup. Open sourcing it:

Nakshatra Saxena

247,814 görüntüleme • 1 ay önce

call me crazy but its pretty clear now. rea + jev is going to change more lives in 2026 than open source ever did. any app goes to rea. jev makes the calls. rea does the work. the app is yours. if this lands on your timeline dont scroll past it. send this to claude code. connect it to rea and jev. thats it. thank me later. most people will ignore this. the ones who dont will be fine. simple as that.

call me crazy but its pretty clear now. rea + jev is going to change more lives in 2026 than open source ever did. any app goes to rea. jev makes the calls. rea does the work. the app is yours. if this lands on your timeline dont scroll past it. send this to claude code. connect it to rea and jev. thats it. thank me later. most people will ignore this. the ones who dont will be fine. simple as that.

Archive

39,148 görüntüleme • 2 gün önce

This is absolutely f*cking insane. you can put a $0.042-per-million-token model in front of Claude and let it decide what Claude ever has to see. that's Jev signal routing, and the trick is stupidly simple: Jev takes the first look at everything. Claude only gets the hard cases. instead of: data -> Claude -> tokens burnt $ it's: data -> Jev -> only the unsure ones -> Claude and here's the part people miss. every Jev answer comes with a probability. that's your router: -> Jev is sure? its answer is final -> Jev hesitates? the case goes up to Claude set the cutoff once, by testing on your own data, not by guessing. 3 repos that already do the routing for you: -> duckdb-jev: route your data. Jev labels every row straight from SQL, up to 1,000 calls in one request -> quicksilver: route your files. Jev checks all 187 files in parallel and Claude gets the 4 that matter. ~2.4k tokens instead of ~26k -> jev-router: route your models. before every message Jev decides simple or hard and sends it to the fast model or the strong one. works with your normal Claude login where this pays off right away: -> support tickets -> your inbox -> lead lists -> messy spreadsheets -> comment moderation on a public benchmark Jev labeled 1,000 rows for $0.015. Claude charged $0.80 for the same job. faster. cheaper. way fewer tokens burned. Jev sorts the mail so the genius only opens what matters. Claude thinks. Jev routes. code does the job.

This is absolutely f*cking insane. you can put a $0.042-per-million-token model in front of Claude and let it decide what Claude ever has to see. that's Jev signal routing, and the trick is stupidly simple: Jev takes the first look at everything. Claude only gets the hard cases. instead of: data -> Claude -> tokens burnt $ it's: data -> Jev -> only the unsure ones -> Claude and here's the part people miss. every Jev answer comes with a probability. that's your router: -> Jev is sure? its answer is final -> Jev hesitates? the case goes up to Claude set the cutoff once, by testing on your own data, not by guessing. 3 repos that already do the routing for you: -> duckdb-jev: route your data. Jev labels every row straight from SQL, up to 1,000 calls in one request -> quicksilver: route your files. Jev checks all 187 files in parallel and Claude gets the 4 that matter. ~2.4k tokens instead of ~26k -> jev-router: route your models. before every message Jev decides simple or hard and sends it to the fast model or the strong one. works with your normal Claude login where this pays off right away: -> support tickets -> your inbox -> lead lists -> messy spreadsheets -> comment moderation on a public benchmark Jev labeled 1,000 rows for $0.015. Claude charged $0.80 for the same job. faster. cheaper. way fewer tokens burned. Jev sorts the mail so the genius only opens what matters. Claude thinks. Jev routes. code does the job.

kiosa

11,388 görüntüleme • 9 gün önce

You can now classify documents with open-weight VLMs at ultra-low cost with our TypeSafe AI Jev-compatible API in the VLM Run gateway! $1 buys you 6700+ pages, and the full 1,651-page OmniDocBench run cost 25 cents. It reads the page as pixels (no OCR->LLM hacks) and hands back one typed, calibrated decision per page - ~180ms p50 e2e. Jev really opened developers' eyes to re-thinking how we process data at the cost-pareto front. A week later we're bringing that to our APIs with vision as a first-class citizen. Try our gateway today - free to sign-up and try!

You can now classify documents with open-weight VLMs at ultra-low cost with our TypeSafe AI Jev-compatible API in the VLM Run gateway! $1 buys you 6700+ pages, and the full 1,651-page OmniDocBench run cost 25 cents. It reads the page as pixels (no OCR->LLM hacks) and hands back one typed, calibrated decision per page - ~180ms p50 e2e. Jev really opened developers' eyes to re-thinking how we process data at the cost-pareto front. A week later we're bringing that to our APIs with vision as a first-class citizen. Try our gateway today - free to sign-up and try!

Sudeep Pillai

20,816 görüntüleme • 1 ay önce

best coding agent use case for Jev: enforcing rules a linter can't coding agents tend to break rules and some rules can't be codified Jev can now score every turn against such rules and tell the agent what to fix asap open-source:

best coding agent use case for Jev: enforcing rules a linter can't coding agents tend to break rules and some rules can't be codified Jev can now score every turn against such rules and tell the agent what to fix asap open-source:

Ohans Emmanuel

118,833 görüntüleme • 1 ay önce

Jev is INSANE 😳 you can use Jev for FREE on OpenRouter it scanned 471 news stories in 31.9 seconds and picked 15 brands worth jumping on - 471 headlines scanned - 15 brand opportunities found - 31.9 seconds - $0.0065 total cost > Claude Opus 5: 17/471 > cost: $0.386 > roughly 1,650x cheaper per headline try Jev here:

K2S

15,167 görüntüleme • 1 ay önce

I built JevSearch, search the web & validate your results with Jev. Give a query and selection criteria, use Browserbase search to get the t25 results, then Jev scores and returns the t5 results. Jev often chooses urls outside of the initial top 5 as more relevant.

I built JevSearch, search the web & validate your results with Jev. Give a query and selection criteria, use Browserbase search to get the t25 results, then Jev scores and returns the t5 results. Jev often chooses urls outside of the initial top 5 as more relevant.

Kyle Jeong

60,133 görüntüleme • 1 ay önce

Tested Jev vs GPT-5.6 for predicting my taste in books. I used my 1,000 Goodreads ratings as starting data and held out 100 to test. Then I asked both models to guess which would be 5 stars. Jev was slightly more accurate, 53x cheaper, and 25x faster 🤯

Tested Jev vs GPT-5.6 for predicting my taste in books. I used my 1,000 Goodreads ratings as starting data and held out 100 to test. Then I asked both models to guess which would be 5 stars. Jev was slightly more accurate, 53x cheaper, and 25x faster 🤯

Justine Moore

27,290 görüntüleme • 1 ay önce

Introducing Jev Plays Minecraft! A 24/7 livestream where Jev attempts to defeat the Ender Dragon, one decision at a time. →

Introducing Jev Plays Minecraft! A 24/7 livestream where Jev attempts to defeat the Ender Dragon, one decision at a time. →

Jarrod Watts

53,441 görüntüleme • 1 ay önce

Jev dropped and people immediately started doing stupid sh*t with it people gave this thing trading bots, browsers, Doom, drones, dinosaurs and tax forms and basically said: “you decide.” here’s what happened: > jev-trader Jev gets a new Monad block every ~300ms and decides whether to place a live limit order. no essay. just the decision. 1,911 stars ▸ ⁠ > jev-ultrafast a browser agent where Jev decides every click. the text model only wakes up when something actually needs to be written. 16,758 stars ▸ ⁠ > jev-doom-agent someone compiled actual Chocolate Doom to WebAssembly and let Jev make the tactical decisions every frame. yes. Doom. ▸ ⁠ > jev-t-rex-runner remember that stupid Chrome dinosaur? now Jev plays it. jump → duck → run → repeat ▸ ⁠ > typesafe-chess Jev went against a real chess search engine. two games. colors swapped. the search engine won both — and overruled Jev’s first instinct on roughly half the moves. ▸ ⁠ > jev-drone camera → Jev → drone. a simulated quadrotor has to clear five stations while Jev looks at the situation twice a second and decides what happens next. ▸ ⁠ > tax-doc-classifier then someone gave it IRS forms. 261 documents. 100% strict accuracy. roughly $0.001/page. ▸ ⁠ > killmyidea this one is evil lol tell it your startup idea. Jev looks at it from different angles and gives you: KILL / FIX / SHIP ▸ ⁠ > jev-curate throw huge Parquet / JSONL datasets at it. Jev judges 1,500+ rows/sec and keeps only the stuff that passes your rules. ▸ ⁠ > pg-jev and now it’s inside PostgreSQL. ask questions about your own tables in plain English → get the decision back. ▸ ⁠ and this is the weird part: none of these need Jev to write you a beautiful paragraph. they need it to look at a situation and pick: BUY / WAIT CLICK A / CLICK B JUMP / DUCK KILL / FIX / SHIP KEEP / DROP that’s basically the whole Jev idea. LLMs think and write. Jev decides. code does. full setup + my three-question Jev test below

Jev dropped and people immediately started doing stupid sh*t with it people gave this thing trading bots, browsers, Doom, drones, dinosaurs and tax forms and basically said: “you decide.” here’s what happened: > jev-trader Jev gets a new Monad block every ~300ms and decides whether to place a live limit order. no essay. just the decision. 1,911 stars ▸ ⁠ > jev-ultrafast a browser agent where Jev decides every click. the text model only wakes up when something actually needs to be written. 16,758 stars ▸ ⁠ > jev-doom-agent someone compiled actual Chocolate Doom to WebAssembly and let Jev make the tactical decisions every frame. yes. Doom. ▸ ⁠ > jev-t-rex-runner remember that stupid Chrome dinosaur? now Jev plays it. jump → duck → run → repeat ▸ ⁠ > typesafe-chess Jev went against a real chess search engine. two games. colors swapped. the search engine won both — and overruled Jev’s first instinct on roughly half the moves. ▸ ⁠ > jev-drone camera → Jev → drone. a simulated quadrotor has to clear five stations while Jev looks at the situation twice a second and decides what happens next. ▸ ⁠ > tax-doc-classifier then someone gave it IRS forms. 261 documents. 100% strict accuracy. roughly $0.001/page. ▸ ⁠ > killmyidea this one is evil lol tell it your startup idea. Jev looks at it from different angles and gives you: KILL / FIX / SHIP ▸ ⁠ > jev-curate throw huge Parquet / JSONL datasets at it. Jev judges 1,500+ rows/sec and keeps only the stuff that passes your rules. ▸ ⁠ > pg-jev and now it’s inside PostgreSQL. ask questions about your own tables in plain English → get the decision back. ▸ ⁠ and this is the weird part: none of these need Jev to write you a beautiful paragraph. they need it to look at a situation and pick: BUY / WAIT CLICK A / CLICK B JUMP / DUCK KILL / FIX / SHIP KEEP / DROP that’s basically the whole Jev idea. LLMs think and write. Jev decides. code does. full setup + my three-question Jev test below

kiosa

67,916 görüntüleme • 1 ay önce

JEV ENGINEERING JUST CUT A CLAUDE LOOP FROM $765/MONTH TO $3.02 the expensive part isn’t always writing code. a busy overnight loop can burn ~600 decisions just asking what to do next, whether a command is safe, or if the task is finished. trigger → Jev → allow / stop / wake → Claude only builds when needed at roughly 4,000 tokens per decision, those checks can cost ~$25.50 a night on Fable 5.1. Jev handles the same decision layer at $0.042 per 1M input tokens with output free. over 30 nights that moves the decision bill from ~$765 to $3.02. batch multiple questions into one call and it falls again to about $1.08/month. that’s the part i care about: Claude keeps the expensive work that actually needs intelligence, while Jev handles the hundreds of tiny judgment calls around it.

JEV ENGINEERING JUST CUT A CLAUDE LOOP FROM $765/MONTH TO $3.02 the expensive part isn’t always writing code. a busy overnight loop can burn ~600 decisions just asking what to do next, whether a command is safe, or if the task is finished. trigger → Jev → allow / stop / wake → Claude only builds when needed at roughly 4,000 tokens per decision, those checks can cost ~$25.50 a night on Fable 5.1. Jev handles the same decision layer at $0.042 per 1M input tokens with output free. over 30 nights that moves the decision bill from ~$765 to $3.02. batch multiple questions into one call and it falls again to about $1.08/month. that’s the part i care about: Claude keeps the expensive work that actually needs intelligence, while Jev handles the hundreds of tiny judgment calls around it.

Gipp 🦅

25,081 görüntüleme • 1 ay önce

Made a real-time slop detector with jev as you scroll

Made a real-time slop detector with jev as you scroll

Robin Bilgil

790,707 görüntüleme • 1 ay önce

Here's another JEV TIP in honor of JEVDAY Jev can answer as many questions as you can fit into context in parallel. You can ask hundreds in one call, and since output is free, why not? 100 questions on a 32k token input document: ~$0.00001 per question ~1ms per question

Here's another JEV TIP in honor of JEVDAY Jev can answer as many questions as you can fit into context in parallel. You can ask hundreds in one call, and since output is free, why not? 100 questions on a 32k token input document: ~$0.00001 per question ~1ms per question

Nathan LeClaire

19,292 görüntüleme • 19 gün önce

This is f*ckin awesome. A Stanford team pairs JEV with Claude Code to sort 75 billion data points every 11 minutes. JEV runs a cheap first pass on everything. Claude only gets the hard cases. Faster, cheaper, way less compute burned.

This is f*ckin awesome. A Stanford team pairs JEV with Claude Code to sort 75 billion data points every 11 minutes. JEV runs a cheap first pass on everything. Claude only gets the hard cases. Faster, cheaper, way less compute burned.

kiosa

63,141 görüntüleme • 1 ay önce