i made a smart calculator notebook using jev it can calculate ANYTHING!! 😅
Core Concepts
Text-only input
Jev evaluates strings, JSON objects, and arrays of text; images, audio, and video are not supported and must be pre-processed.
- Category
- Core Concepts
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- Related terms
- 3
- Directory entries
- 2
- Docs
- docs.typesafe.ai
- Added
- 2026-09-24
Definition
State must be a string, JSON object, or array of text values. Non-text inputs such as images, audio, video, or binaries need to be converted to text or structured fields before they are sent.
English is the primary training language and where accuracy is best. Other languages, including CJK scripts, are accepted but currently less accurate, so test on your own content and watch confidence when routing.
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StateThe content a request asks Jev to evaluate: a string, a named object, or an array of messages, shared by every question in the request.Core ConceptsLanguage supportEnglish is Jev's primary training language; other languages are accepted but less accurate, so test before relying on them.API & ModelsJaggednessThe documented set of jev-1.13 failure modes — literal reading, counting, dates, indirection, context rot — each with a guardrail.Evaluation & Training
From the directory
How to shape what Jev evaluates: a string, a named object, or an array of messages. Every question in a request sees the same state and is evaluated independently.
Practices & PatternsDocs#official#docs#state
Official
The model card for jev-1.13.0: $42 per billion input tokens with free output, a 64k context, 250k tokens per second, and how to list the models your account can call.
Sites & GuidesDocs#official#docs#models
Official
From the community
Posts from builders shipping with Jev right now.
Jev Calc: a notebook that calculates anything
Day-one notes from a skeptic, in Chinese
一些关于 Jev (@typesafeai) 的 notes 研究了一天 Jev，带来的新鲜感迅速回落，这好像就是一个更快的通用分类器/决策器，LLM 完全可以做到。 而且因为不了解模型背后的参数规模（应该不会很大），世界知识可能不一定有常规 LLM 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
Search and tagging on keep.md
Cloudflare Workers has Jev now so I'm putting it to the test on keep.md - 7x faster search rerank compared to the current hybrid - 50x faster tagging of content vs GLM 4.7 Flash with no failures
A filter for reply-guy comments
Pro tip: You can use Jev to remove annoying reply guy comments that X seems to always miss. Takes 5 minutes in Astra with the docs and an API key.
A Downloads folder that sorts itself
Jev unlocks SO many awesome new ideas. I built a macOS app that monitors my Downloads folder along with a customisable set of rules. Is the downloaded file an invoice? Move it to a special folder with the correct filename. No other LLM calls involved - just Jev!
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 Show more