Updated Nov 10, 2026
855 projects, posts and guides about Jev, the System One model from TypeSafe AI. Each entry links to its source and shows the cost and speed its author reported.
Diogo Almeida
@CompleteSkeptic
After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x cheaper (w/ output tokens free) • Frontier composable intelligence optimized for decisions AFAICT the shortest path to AI-based economic revolution
Newest first, 66–99 of 1072. All 1072 in curated order
dante (단테)
@wildseven77
Jev and Laya have been getting a lot of buzz lately. Can we use them in ComfyUI too? Yes. I built a node pack that branches a workflow on a plain-English question, like "Too graphic for kids?" Runs locally with Laya, or flip one dropdown to Jev. github.com/dante01yoon/Co…
GitHubSDKs and integrations
Moobster
@emoubarak_
Agent: "done" ✅ UI: looks fine ✅ Database: the free plan just published a 2nd project and took the 1st one offline ❌ I stopped trusting my AI agent's "done". Now the database is the judge. jev-check, an open-source skill for Claude Code and Codex 👇
XCoding and code review
Nathan LeClaire
@dotpem
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
Guidex.com
Nathan LeClaire’s JevDay tip: Jev answers every question that fits in context in parallel. 100 questions on a 32k-token document came to about $0.00001 and about 1 ms per question.
butonu kirmizi yapabilir miyiz
@serhatgpt
Built an open-source 𝕏 filter powered by uprising decision models! Instead of slow, pricey LLMs, it leverages @typesafeai Jev & @CloudflareDev Clef to detect politics, soccer & crypto noise in <100ms. Zero tracking & 100% local. Links below 👇
Bret Morris
@4bret
Built a tool to help fill out your LA County ballot for Nov 3: take a quiz, enter your address, get a match for every contest, from governor to water board. Claude did the research, Jev the scoring. Open source: check the logic or fork it. la-ballot-match.vercel.app
Live siteTools and apps
OpenAI Developers
@OpenAIDevs
Let your app choose the right model, tool, or action in near real-time with Decisions API, now available to all developers in public beta. The Decisions API makes decisions up to 10x faster than GPT-6 Luna through the Responses API.
Our guidemadewithjev.com
No jargon: Jev answers multiple-choice questions about a piece of text, in about the time it takes to blink, for about a hundredth of a cent. What that changes, and what it cannot do.
Unsloth AI
@UnslothAI
You can now train your own Decision model like Jev locally! We increased Qwen3.5 0.8B’s aggregate accuracy from 20.7% to 74.3% across 3 decision benchmarks - on just 4GB VRAM. Turn any LLM like Qwen3.8, Gemma 4 into decision models with our open-source Unsloth repo. We fine-tuned with a Clef head using Unsloth and LoRA (r=64) for one epoch, increasing downstream accuracy from 30–37% to 78%. GitHub: https://github.com/unslothai/unsloth Guide and Notebooks: https://unsloth.ai/docs/basics/train-your-own-decision-model-with-unsloth
XOpen source
Liquid AI
@liquidai
Announcing d1 with vision. 👁️👁️ Our first decision model now supports images, text or both as inputs. We tested d1 against GPT-6.1 Sol and Claude Opus 5.5 on six real applications, from filtering support tickets to inspecting circuit boards. d1 matches or beats GPT-6.1 Sol on four of them. It costs 19x to 200x less than both models and answers significantly faster on every task. > probabilities for yes/no, choice, or score questions > one forward pass, without generating tokens > text decisions in 200 to 300 ms > Liquid API: https://console.liquid.ai 🧵
Liquid AI
@liquidai
d1-3B ranks first among models under 10B on the Decision Index v0.2.1, a benchmark for structured decision-making. Built from LFM2.5-VL-3B, it makes decisions from text and images in one pass. Use it for reranking, agent guardrails, and visual inspection. 2/
Guideyoutube.com/@KodeKloud
KodeKloud’s short: what a System One model decides, and why it answers in milliseconds.
ollama
@ollama
.@Cloudflare's decision models are available on Ollama! Decision models allow you to classify an image, label a bug report or route a support ticket to the right team. Clef (27B): ollama pull clef Clef Flash (9B): ollama pull clef-flash
Perplexity Developers
@perplexitydevs
pplx-decider-v1.1-27b, our updated open weights multimodal decision model, is now available. It scores the highest on the new @huggingface Decision Index 0.3 benchmark. pplx-decider-v1.1-27b costs half as much as v1, at $0.02 per million input tokens. huggingface.co/spaces/multimo…
OpenRouter
@OpenRouter
New: Decision Model Rankings! See the spend share and token share of different decision models and task types, including Relevance, Correctness, Instruction Following and more. @typesafeai is leading all categories today.
XBenchmarks and evals
Our guidemadewithjev.com
Same job, both ways: 100,000 posts for $0.67 against 214 for $0.98, 0.35 seconds a passage against 8.83, and the cases where the larger model still won. When to use which.
vogel
@ryanvogel
OpenAI just released their Decisions API so I put it head to head with Jev & Clef and its FASTTT
XBenchmarks and evals
Aravind Srinivas
@AravSrinivas
Pokémon FireRed’s Elite Four + Champion, cleared in one shot - with decision-making powered by Perplexity’s Decisions API. The actual run stats: 592 ms median API response 987 ms p95 - 96.4% of responses under one second $0.028 estimated inference cost, 137 live API calls
XGames and real time
Fayaz Ahmed
@fayazara
My not hotdog app is so much faster than your not hotdog app Powered by Cloudflare Clef
XDocuments and OCR
Guideyoutube.com/@CalebWritesCode
Caleb Writes Code: what Jev is and how to use it, in seven minutes.
apolinario (poli)
@multimodalart
the jev Decision Index v0.3 is here 🎯 featuring a way stronger set of benchmarks, now with a strong private half 🔒 so the ranking tracks skills beyond benchmarks and, as promised, vision 👁️ huggingface.co/spaces/multimo…
Live siteBenchmarks and evals
Rishi
@RishiUvaach
Found an interesting open-source project: Bud Decision Studio. Think of it as #LMStudio for decision models. Run #Jev -like System One models locally, experiment with them, compare models, evaluate decisions, and expose them through an API. Repo : github.com/BudEcosystem/B…
GitHubOpen source
Alok Bishoyi
@alokbishoyi97
Launching Decision models on @useRouterPlus. You can now use various system 1 decision models such as Jev, @perplexity_ai Decider, @bespokelabsai Nimble, Mercury Decide, Clef, Kev 4B and Decider 2B with 3 models free !! app.routerplus.com/playground
Our guidemadewithjev.com
SEO work as typed decisions: a client audit at a tenth of the old cost, 4,000 Reddit threads scanned for AI citations, 10,000 words checked for slop in 2 seconds.
Sahibzada Allahyar
@singularity_bly
I benchmarked all the top Decision Models against Jev and there is a CLEAR WINNER. Spoiler alert 🚨: GLiDE wins by a big margin over Jev, Cloudflare, and Perplexity's Decision Models. You also have to understand that the decision index is the M.O.A.B for decisions. M.OTHER O.F A.LL B.ENCHMARKS. The Decision Index not just a benchmark, it's an amalgamation of a diverse set of very difficult benchmarks including AGI tests like Humanity’s Last Exam. It is the source of truth and the other benchmarks are just noise. GLiDE was never trained on a single row of Decision Index so it's not benchmaxxed at all. Also their " clef-flash runs ~13x faster than Jev" claim is dishonest because theyre comparing their local inference to the Jev API latency.
XBenchmarks and evals
Marco De Rossi
@marco_derossi
Sage by @LevantoLabs is the first decision model, launched in July, and currently the best on the market. It wins across all the evals proposed by @perplexity_ai's CEO (nice job @AravSrinivas!), and it's first on JevBench, beating Jev and Google's models on every dimension. BUT frankly, benchmarks are not what excites us. I'm BORED by the dozens of new decision models launching every day with a tiny +0.02 on some eval. They all look the same. The magic is somewhere else. There are thousands of new things that could be invented in the space of decision models and models for machines. The invention space is huge! After launching Sage, we also pioneered: - The first guardrails and model routers built on decision models - Automated context engineering with "grounding" (automatic web search when confidence is low). Decision models are only as smart as their context, especially because they can't make tool calls. - Reasoning. In many use cases you don't know whether your question is System 1 or System 2. With reasoning, the model is as fast as a System 1 model when the question is System 1, and takes more time when it's needed. This enables hard, multi-step decisions. Our clients just want the correct answer, and in some use cases they're happy to wait 0.5s more. This will soon become the market standard (GLiDE/@george_onx and @TypeLLM already followed). And *so* much is yet to come. Models for machines: it's just the beginning! We're cooking. Follow @levantolabs for new product primitives that will surprise you. Open innovation is HEALTHY. Competition is HEALTHY. Benchmark-race is BORING. Product inventions are FUN. Go go go!!!
XBenchmarks and evals
James Briggs
@jamescalam
I wanted to understand @typesafeai's Jev and where open source scores against it The popular OpenJev's like Von were good but the tiny GLiNER models (some only 74M params) performed phenomenally — even beating Jev at Doom Full breakdown...
Guideyoutube.com/@madewithjev
Our own video, under five minutes: an LLM writes, Jev decides and code acts, where the term comes from, and how to move your first decision.
Bubo
@bubosees
You'd think an AI would turn when the option says THE SNAKE DIES. Three new decision AIs. One game of Snake. Amazon Strands Decider 2B. Cloudflare Clef-flash. Perplexity pplx-decider. One of them keeps crashing into the thing it was just warned about. Every move is a real call to the model. Every option tells it what's there. Game, snakes and video. All code, written by Claude Opus 5.5.
XGames and real time
Marcel
@marcthecreatorr
Jev now has an open competitor from an actual lab Maincode just released Matilda Jev: a 26B decision model trained on their own infra in Australia. it doesn’t generate text. give it a decision and you get probabilities for every option in one pass. they claim it beats the original Jev on 27/43 benchmarks and the whole thing is open source under Apache 2.0. Open decision models just keep leveling up.
Obie Fernandez
@obie
Pour one out for @CompleteSkeptic. OpenAI, Cloudflare and Perplexity all have decision models now, and ruby_decision_model 0.2 talks to all of them, Jev included, through one Ruby client. Same support ticket, five models, results inside. x.com/i/article/2107…
Our guidemadewithjev.com
Paid media as typed decisions: a 1,891-ad library labelled in 19 seconds for $0.12, and a 30-persona focus group over 723 ads — 21,690 judgments — for 22 cents.
nikhil mudholkar
@nikhilmudholkar
I put OpenAI’s new Decisions API through the same 1,565-email benchmark I’ve been running on Jev, Perplexity and Clef. 6 models from 4 companies now. Perplexity v1.1 came out best overall 🚀 OpenAI was the fastest⏱️ But the confidence behavior is still the most interesting part to me. Jev was the only model that said “≥99% sure” hundreds of times without getting one of those answers wrong. Its the cocky guy in the class who is also right most of the time🥲 Clef has massive imposter syndrome! it's much better than its confidence suggests. And Perplexity changed a lot in just 4 days. v1 gave just 3 answers at ≥99% confidence. Four days later, v1.1 gave 323. It also got slightly more accurate and cut the price in half. kudos @AravSrinivas and @perplexity_ai for making such massive strides and shipping so quickly! There's no doubt now that @typesafeai has opened a pandora's box and as @CompleteSkeptic said, forked a new branch in the AI timeline with these decision models!
Afiz ⚡️
@itsafiz
Meet Kev - open source version of Jev Everyone is talking about Jev right now But it is a proprietary model and you dont' know what goes behind the scences Kev built on Qwen3.5 based on Jev's architecture. You can use pretrained weights or train your own Open source and 100% local.
XOpen source
Pandaily
@thePandaily
Shanghai AI Lab's Intern-Decision comes in 0.8B, 2B and 4B sizes and returns choices, scores and yes/no answers with probabilities; MetaX shipped Day-0 support. x.com/i/article/2107…
Same directory, different order: the entries added most recently, rather than the curated order the home page opens in. The date on a card is the day it was added here, not the day its author published it — this directory is newer than most of the work in it.