What people post on X about Jev

Paone

@paonx_eth

i sent a crawler through github's new ai repos from the last 30 days. this is what it looks like 1 crawler turns into 128 2,000 repos, every readme, every word it steps on each one goes to jev with one question: is this worth your time? 99.3% got thrown out. wrappers, copies, empty readmes, lists of lists 9 survived: 01 colibri · runs a 744b model on 16gb of ram and a big ssd. slow, but it's yours 02 voicebox · clone a voice from a few seconds of audio. 23 languages, nothing leaves your machine 03 BrowserSkill · tencent. claude code or codex works in your logged-in browser while you keep working 04 security-audit-skill · the skill cloudflare's bug-hunting harness grew from 05 open-code-review · alibaba's internal ai code reviewer. ~1/9 the tokens of claude code on the same model 06 agent-skills · 25 senior-engineer workflows: /spec /plan /build /test /review /ship 07 OpenResearch · turns claude code or codex into a research agent: papers, hypotheses, experiments 08 WeKnora · tencent. drop in your docs, get rag answers, an agent and a wiki that maintains itself 09 ECC · 68 agents and 293 skills for claude code, codex and cursor. 272k stars 4 of the 9 come from alibaba, cloudflare and tencent. big tech is open-sourcing the ai tools it runs on itself links in the reply. save this

Burak Karakan

@burakkarakann

I built a query layer that automatically routes the queries to one of the configured query engines using Jev, all running on top of Iceberg. Fast decision models unlock interesting use cases indeed. Should we open-source this?

Dr. Shawn

@aroogle

I’ve built an AI system using Jev and Groq that turns your speech into powerful visual slides, charts and animations as you talk with 70-300ms latency. Should I open source it or charge people to use it so that I can buy more hedera-hashgraph:native ? Kind of love the addictive feeling of open sourcing things… just feels so legendary

Mastra

@mastra

Last week, we launched: 1/ Classifiers with Jev 2/ Jira, GitLab and incident.io integrations for Mastra Factory 3/ Memory hooks 4/ VPC-isolated Postgres for Mastra platform + a lot of smaller improvements.

Pedro Martins

@nikuscs

Having some fun doing my own Grok Bot @bot ( Dots, Muse ) alternative with @tan_stack start, @pidotdev + @Cloudflare durable objects! 💅 - Multi-harness Support - Multi Decision Room Routing ( Jev, LLM Judge, Roundtable ) - Memory for Bots, Rooms & Global - Reactions 👍 - Daemon runs locally + web on cloudflare - File Support with R2, Room data & Bot Data exportable on CF durable. Will open-source next week hopefully, so give a follow & stay tunned. I was going to use some open-source alternatives or fork them, but most of them are damn sloppy, my ideia is to use this for myself since OpenClaw & Hermes lack group collaboration & a proper mobile / responsive design. Dots is not available in EU, Grok is "locked" to grok models but for me its still the best in terms of UX/UI overall so congrats to Cursor & Xai Team :p

NatashaTheRobot

@NatashaTheRobot

I built a small AskHIG CLI tool + agent plugin to help the agent load only the RELEVANT HIG guides into context via an /askHIG command. It uses @typesafeai Jev to decide which guides, so all you need is a personal typesafe API key and you're all set! I would open source it, but don't want to get in trouble with 🍎... If you'd like access, reply with your github username in the comments and I'll add you to the repo!

Ayush Gupta

@madmecodes

Found this pretty interesting repo: herdr + jev = agent router You give it a coding task, and it routes it to the right agent + model + reasoning effort based on the task and your available quota. Supports Cursor, Claude Code, Codex, and OpenCode. Basically a load balancer for your coding agents. https://github.com/nidhi-singh02/agent-router Thanks @nidhisinghattri

Aditya Rao

@dev_adityarao

Catching AI agents that secretly collude usually means reading their minds. I just read their chat instead, using Jev by TypeSafe AI It named the colluders 85% of the time. Built for the AI Swarm Dynamics Hackathon by @grove_research & @aidigest_. Thanks for letting people join online, I really enjoyed it!

moub.dev

@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 👇

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 👇

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

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/

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.

vogel

@ryanvogel

OpenAI just released their Decisions API so I put it head to head with Jev & Clef and its FASTTT

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

Fayaz Ahmed

@fayazara

My not hotdog app is so much faster than your not hotdog app Powered by Cloudflare Clef

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.

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!!!

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...

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.

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…

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.

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…