@typesafeai (and System One models in general) have a lot of uses, and fun to play with. New paradigm open to public now. This is a self-driving sim I spun up to test Jev today. Structured sensor state in, typed driving decisions out, steer, brake, overtake, pedestrians, speed Show more
API & Models
Language support
English is Jev's primary training language; other languages are accepted but less accurate, so test before relying on them.
- Category
- API & Models
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- Related terms
- 3
- Directory entries
- 2
- Docs
- docs.typesafe.ai
- Added
- 2026-09-24
Definition
The models page is explicit: English is where accuracy is currently best, and other languages, including CJK scripts, are handled but not equally well. Non-English workloads need testing on your own content.
Confidence is the recommended guardrail in the meantime — watch it closely when routing non-English requests, and keep a human path for the cases that matter.
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Related terms
Definitions that connect to this one.
Text-only inputJev evaluates strings, JSON objects, and arrays of text; images, audio, and video are not supported and must be pre-processed.Core ConceptsConfidence gateA threshold on confidence that decides whether code acts, confirms first, or escalates to a person or a bigger model.Answers & Confidencejev-1.13.0The current versioned Jev build: $42 per billion input tokens, a 64k context, and 250,000 tokens per second.API & Models
From the directory
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
144GitHub stars
Grep by meaning instead of regex: Jev scores every line, meanings combine with AND, OR, and NOT, and one query matches across Japanese, French, German, Spanish, and more.
Tools & Integrations#community#javascript#cli
Community
uehaj/jev-semgrepJavaScript
uehaj/jev-semgrepJavaScriptFrom the community
Posts from builders shipping with Jev right now.
Jev Driving Lab: a playground for System One models
200 rows, 32 template families, and traps, judged in one call
First test with Jev (TypeSafe System One): 200 rows, 32 template families, traps — 'yes' rows with "we'll pass", 'no' rows with 'absolutely, happy to meet'. The single Jev question scored 100%. My 12 dimensions scored 98%. I had designed a task my own question could ace.
jev(): Postgres WHERE clauses in plain language
I think I just cooked something 🔥 jev(): a PostgreSQL extension that searches your whole database in natural language. No index, no embeddings, just one function. WHERE jev(people, 'could work from home') or WHERE jev(people, 'name sounds european') 129 rows judged in ~1s 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
A real-time ad blocker that classifies every DOM element
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
Harness: I made Jev control the player, has access to WASD, space, click, and mouse movements. Astra is the planner that sends instructions to Jev async. Learning: Each time the agent would fail, Astra would add skills as mjs files, that it can draw upon in different scenarios, Show more
Tool calling as classify plus action, back to twelve-factor agents
jev is the best excuse you could possibly have to go re-read 12 factor agents. Tool calling itself can be decomposed into classify+action, if you learn to design ai programs as pipelines that switch breathlessly between classification, structuring data, deterministic code, AND Show more
@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