Jev is WILD I gave it two launch tweets and fed it over 4000 demographic profiles of real survey participants Twelve seconds later, a simulated A/B test tied to actual personas voting on the best tweet you can just do things i made it 100% free (link below)
CommunitySites & Guides
Typed Decisions, Not Chat
A heavily footnoted claims audit that separates documented Jev facts from marketing, including the seed round, third-party tests, and missing transparency.
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- Warmer Sun
- Added
- 2026-09-25
- Last verified
- 2026-09-25
Highlights
- Notes the $40 million seed led by DCVC and that the reported $200M valuation rests on one anonymous source.
- Recaps Every's 777 judgments in under 0.7 s at about a quarter cent, with a defect test missing one of seven.
- Cites OrcaRouter's reading of 67.8% mean agreement against 74.1% for the best comparator.
- Lists missing items: no public paper, parameter count, weights, residency table, or DPA.
Watch out
Independent-leaning but long and heavily footnoted with some second-hand figures; the site also promotes its own product.
Reactions & coverage
Posts, threads, and videos about this entry from around the web.
X: An A/B test against 4,000 personas
X: Ad creatives from filtered assets
Jev is really good at content filtering and asset selection. DeepSeek + Higgsfield turn the selected assets into ad creatives.
X: A shortlist from a competitor swipe file
JEV makes competitor research feel like a cheat code. Give it your competitors’ ads. Break them down by hook, angle, offer and format. Then turn recurring combinations into a shortlist for your next creative test. From an endless swipe file to “here’s what we should try next.” Show more
x.com/i/article/2101…
X: 1,315 posts across eight dimensions
Jev classified 1,315 X posts for about $0.086 in estimated model cost 😂 seeing everyone's Jev demos made me want to build something for my own content research. i'd collected a lot of posts, but figuring out what they had in common still meant opening them one by one and 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
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A release guide with eval tables, pricing, curl and Python examples, and fit boundaries for Jev's early access.
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From the community
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jev(): Postgres WHERE clauses in plain language
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@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
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I build an undetectable realtime adblocker extension with typesafe It checks every dom element and classifies as ad/non-ad and removes it if true Extremely fun to work with, expecting an incredible shift in how AI is being used in the future
@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
Jev plus Astra beats the Ender Dragon for under a dollar
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Tool calling as classify plus action, back to twelve-factor agents
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@dillon_mulroy
i think jev is resonating with devs so well b/c it unlocks so many opportunities for composing ai into systems and products rather than ai _becoming_ the product/system really does feel like it was a missing primitive
Why Jev encodes a state and outputs distributions instead
Jev is one of the more interesting model launches I have seen recently because it asks a very simple question: Why are we using autoregressive LLMs as insanely expensive if statements inside software? The easiest way to think about it is: LLM: text -> generate tokens 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