Breaking: Browser Use + Jev = Ultrafast ⚡ Findings flights took 7s and cost only $0.0039 🤯 > new action space every step > DOM state space > small LLM fallback to type (this video is at 1x speed btw) Built a tiny open source browser agent. try it below ↓
Open Alternative to Jev
An Apache-licensed Python library that reads option-token probabilities from open-weight models through Transformers or vLLM, giving Jev-style typed decisions in one forward pass without an HTTP server.
- Category
- Repos & SDKs
- Published by
- Community
- Author
- ikermoel
- Added
- 2026-09-22
Tagscommunitypythonopen-modelscalibrationbenchmarks
Highlights
- On a 400-case typed-decisions benchmark, Qwen3.6-27B scored 73.7% accuracy with ECE 0.020 versus Jev 1.13.0 at 72.7% and ECE 0.144.
- Probabilities were five times closer to the gold distribution (KL 0.27 versus 1.44), at 582 ms per case versus 710 ms for Jev.
- On RACE-H, packing the shared state once processed 186,898 tokens at 4.55 questions/s versus 468,583 tokens at 1.66 questions/s one at a time.
- It replaces the library, not the endpoint: the package runs in-process and there is no HTTP server or drop-in API for the official Jev SDK.
- A live Hugging Face Space demo runs Qwen3.5-4B with no install, answering from the next-token distribution restricted to the given options.
Quickstart
bash
pip install open-alternative-jev
pip install "open-alternative-jev[vllm]"
pip install "open-alternative-jev[quant]"Watch out
Apache-2.0. Needs Python and your own GPU for the larger models; it is a library rather than an endpoint, packed answers can shift with question order, and benchmarks compare modes of an open model, not Jev's training.
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From the community
Posts from builders shipping with Jev right now.
Browser Use Ultrafast, powered by Jev
A really smart switch statement
hype-free explanation of jev: jev does not replace gpt / claude jev is just a *really* smart switch statement like if 2016 ml classifiers got 2026 levels of intelligence it's a new* type of tool that will make a lot of workloads insanely fast, cheap, and accurate * = and by Show more
@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
When a designer gets Jev
when a designer gets access to Jev
Full Jev video tutorial
Full Jev Tutorial What it is, how you can build with it and what new applications it can unlock → 0:00 Intro → 0:34 Jev explained → 4:06 API setup → 5:59 Demo 1: Voice-controlled browser → 11:33 Demo 2: AI memory → 17:27 Demo 3: YouTube predictor
The case against Jev-scored compaction
This is a terrible compaction strategy that fundamentally doesn't understand how compaction and context management work. Seems like a lot of people are confused so let's break this down. 1. Compaction isn't a filter The role of compaction is to clean up history to keep the Show more
found the perfect use case for @typesafeai Jev: instant compaction in 2026, why is compaction still a summarization prompt? Jev can make it instant by scoring every tool call and dropping what’s irrelevant
Classifying rows in DuckDB
I made a DuckDB extension where you can use @typesafeai 's Jev to do quick classification of rows in any csv/parquet file or duckdb table about 10sec for 1k rows ~ better than using an LLM, way more ergonomic than a classifier game-changing for data analysis!
