Research & data
124 builds · page 3 of 4
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jev-korean-benchmark
Small Korean/English sample study with recorded responses, including medical-text questions; not a clinical validation.
mahlernim · Research & data
mahlernim
GitHub
Research & data
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- 0448
jev-eval
Independent Jev versus GPT-5.6 Terra comparison on three labeled classification tasks, reporting accuracy, calibration, latency, and cost.
4esv · Research & data
4esv
GitHub
Research & data
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jev-benchmarks
Reproducible evaluation for calibration, selective risk, and latency.
AbdelStark · Research & data
AbdelStark
GitHub
Research & data
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- 0446
jev-behavior-study
Independent synthetic-task study of Jev 1.13.0 framing sensitivity and failures, with raw responses and offline report checks.
RINNECODER · Research & data
RINNECODER
GitHub
Research & data
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Jev vs. ML
Compares a typed decision model with classical classification pipelines across eight datasets, with a published protocol and an interactive report.
QuicqDev · Research & data
QuicqDev
GitHub
Research & data
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Jev Visual
Educational MLX/Qwen vision-language experiment sharing image context across candidate-scoring questions; its probabilities are not calibrated correctness estimates.
hr98w · Research & data
hr98w
GitHub
Research & data
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jeff
Self-hosted implementation of Jev's System One API on the 400M-parameter GLiFormer model.
logan-markewich · Research & data
logan-markewich
GitHub
Research & data
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Janus
Measures when to use Jev versus other models and routes accordingly.
FirasSX914 · Research & data
FirasSX914
GitHub
Research & data
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- 0441
feelings
BAML language support for an AI if-statement: `.feels()` as a real, typed method backed by a decision model.
BoundaryML · Research & data
BoundaryML
GitHub
Research & data
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choosekit
Scores a finite set of choices with a model you already run in llama.cpp and returns a typed decision with a probability distribution.
NotXf1le · Research & data
NotXf1le
GitHub
Research & data
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Bespoke Nimble
Open data, training recipe, and a 9B model for Jev-style choice and true/false decisions on Apple Silicon or NVIDIA GPUs.
bespokelabsai · Research & data
bespokelabsai
GitHub
Research & data
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1kpapers
1,018 AI papers sorted by topic for $0.08 and published as a site.
@nutlope · Research & data · $0.08 · 256 ms
@nutlope
Site
Research & data
$0.08
256 ms
- 0264
Search and tagging on keep.md
Cloudflare Workers has Jev now so I'm putting it to the test on https://t.co/1fK8HbSmPm - 7x faster search rerank compared to the current hybrid - 50x faster tagging of content vs GLM 4.7 Flash with no failures
@iannuttall · Research & data

@iannuttall
X post
Research & data
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jevlike
A Jev-like architecture, reverse-engineered, to train your own.
@vinnylarouge · Research & data
@vinnylarouge
GitHub
Research & data
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A visual reference finder
I built a visual reference finder with Jev One single prompt → 100 images from Cosmos, NASA, and The Met my new rabbit hole for creative work 🌻
Albiona Hoti · Research & data
Albiona Hoti
X post
Research & data
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openjev-sglang
A public Jev-compatible API on an open model: 64 tasks in under a second.
@ekzhang1 · Research & data
@ekzhang1
GitHub
Research & data
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openjev on Qwen 4B
An MLP trained on top of Qwen 4B that works like Jev.
@justALEXWORTEGA · Research & data
@justALEXWORTEGA
Site
Research & data
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@wmoto_ai
X post
Research & data
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reflex
A small open decision model: state and typed questions in, probabilities out.
Kshetrajna Raghavan · Research & data
Kshetrajna Raghavan
GitHub
Research & data
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- 0184
jev-search
Offline Obsidian search, with an optional Jev rerank you approve first.
jh1373 · Research & data
jh1373
GitHub
Research & data
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@jokull
GitHub
Research & data
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jev-reviewer
Systematic-review data from trial reports, every answer a verbatim quote.
@asofimahmudi · Research & data
@asofimahmudi
GitHub
Research & data
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Classify 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!
@hamiltonulmer · Research & data · ~10 s per 1k rows

@hamiltonulmer
X post
Research & data
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~10 s per 1k rows
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duckdb-jev
Ask a question about every row in SQL, and get a real SQL type back.
Colliber · Research & data
Colliber
GitHub
Research & data
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Giulio Piccolo
GitHub
Research & data
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Jev Capability Atlas
Where Jev holds up and where it breaks, with real API receipts.
Zaious · Research & data
Zaious
GitHub
Research & data
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Which outreach signals book demos
JEV is insanely fast. We gave it a massive dataset based on thousands of outreach messages and asked: Which intent signals generated the most booked demos? 40 seconds later, we had the answer. Cost: less than $0.20. JEV can also rank leads, measure prospect-message fit, and
@pierreeliottlal · Research & data · <$0.20 · 40 s
@pierreeliottlal
X post
Research & data
<$0.20
40 s
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Filtering WIP todos by meaning
Using Jev to filter through my @wip todos It allows me to super quickly find all the instances where I increased revenue, got stuck, switched to a different SaaS provider, etc Things a regular keyword search would never catch
@marckohlbrugge · Research & data
@marckohlbrugge
X post
Research & data
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Natural-language search over Zillow
Jev can serve as better natural language search on websites. It can scan thousands of Zillow listings and classify properties by things you can't normally filter for - e.g. architecture, renovation status, proximity to freeways. This was done in <20 sec and costs $0.18 👇
@venturetwins · Research & data · $0.18 · <20 s
@venturetwins
X post
Research & data
$0.18
<20 s
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Which exam questions come back
JEV IS INSANE. I gave it 80 real exam questions and 297 practice ones. In 80 seconds, it told me which ones are most likely to appear on the real exam and which ones aren’t. All for $0.0256. Can't stop playing with @typesafeai 😁
@hametgholizadeh · Research & data · $0.0256 · 80 s
@hametgholizadeh
X post
Research & data
$0.0256
80 s
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A 26-sheet plan set in 2.9 seconds
Built a construction plan-set classifier with Jev. Proq turns civil and building plan sets into bills of materials using an LLM pipeline we built on GPT-4.1. Jev classified an entire 26-sheet plan set in 2.9 seconds for $0.0052. It matched GPT-4.1 and GPT-6 Astra on 100% of
@hari_trinay · Research & data · $0.0052 · 2.9 s
@hari_trinay
X post
Research & data
$0.0052
2.9 s
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Tocsin
22.8M log lines grouped into patterns, then one question each.
@TPateeq · Research & data · $0.64 · 6 min
@TPateeq
GitHub
Research & data
$0.64
6 min
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Sutro
GitHub
Research & data
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OpenJev Verdict 2.0
A 151M non-autoregressive decision engine, with its numbers published.
Heman10x · Research & data
Heman10x
GitHub
Research & data
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jev-evaluation
Nine experiments and 28 predictions, all fixed before any data.
Will Kelly · Research & data · $12.69
Will Kelly
GitHub
Research & data
$12.69
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visual-jev
Typed decisions over images, not text descriptions of images.
Andrue Anderson · Research & data
Andrue Anderson
GitHub
Research & data
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Kyle Pena
GitHub
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SiliconLabAI
GitHub
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open-spark-jev
Local System One models on Qwen3, for an NVIDIA DGX Spark.
Abhishek Rai · Research & data
Abhishek Rai
GitHub
Research & data
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ChatJev
Driving the classifier as a next-token predictor, one token at a time.
Erik Dunteman · Research & data
Erik Dunteman
GitHub
Research & data
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