Independent · Measured · No promotion
TypeSafe Jev, observed.
Public usage cases grouped by the decision they make, plus latency and cost measurements we ran ourselves on an identical task set. We do not verify what authors claim, and we do not make a page for every post.
Decision types
8 hubsagent loop
Tool, route and guardrail choices mid-loop.
guide in progress → browse casesdocument classification
One call per page, row or record.
browser agent
Element-level choices inside a live page.
game decisions
Enumerated legal moves under a frame budget.
inbox triage
A decision per message, at volume.
guide in progress → browse casestrading decisions
Rules in code, judgement in the model.
guide in progress → browse casessupply chain gate
Allow or refuse, before the code runs.
guide in progress → browse casestext detection
A probability instead of a classifier.
guide in progress → browse casesOne number we stand behind
Full method →Cost per 1,000 decisions · warm n=124 per model
lower is betterJev is the cheapest here, but only by about 1.8× against the cheap baseline — not the 40–400× you see quoted. Against the frontier baseline the gap is about 7×. Accuracy is shown alongside because on these four tasks all three sit at ceiling and accuracy separates nothing.
Warm p50 latency
312.7 ms
against 263.4 ms and 258.8 ms for the two baselines.
Round-trip floor
281–944 ms
A minimal request already costs this much from where we measured. At that distance a single call is dominated by the network, not the model.
Recently indexed
All 336 →- 2026-09-19@kushwho11146Hey Everyone, Just Built : Audit your git diff against YAML coding-standards packs using TypeSafe's Jev model, from a CLI or your AI agent's command/skill. 1 step install: npx @kushwho/jev-codes…132supply chain gate
- 2026-09-19@jiayaoctrl-f has never understood a single query. It matches strings. This one scores meaning: every sentence on the page gets a probability with @typesafeai's Jev, and walks you through the hits.…437document classification
- 2026-09-19@acharyaagamyaI made a Magic Jev Ball for code reviews 🎱 Click it on any GitHub PR and ask: "should I approve this?" It checks CI, diff size, and reviews, then lets @typesafeai Jev decide your fate in ~200 ms No…91supply chain gate
- 2026-09-18@maubaronjev is insane 🤯 here is jev playing smash bros against itself he is controlling all 4 different characters. and literally deciding whats the best move to play against itself all within a fraction of…300.3kgame decisions
- 2026-09-18@wuyang_zhoubtw this is what you get if you ask Jev to play Minecraft with GPT-6 Astra. I still can’t believe it45.8kgame decisions
- 2026-09-18@wiley_laddTypeSafe AI is challenging the industry’s reliance on large language models for every stage of the agentic stack with the launch of Jev, a specialized “System One Model” designed exclusively for…202inbox triage
What this site is
Two parts, and they support each other. The case index collects public builds and groups them by decision type, so you can find the one that looks like your problem rather than the one with the most views. The benchmark page runs Jev and two chat models on an identical task set and publishes every raw response, so you can recompute the numbers instead of trusting them.
The grouping is the useful part of the index. “Someone used it to sort files” and “someone used it to drive a browser” are not the same kind of fact; what transfers between projects is the shape of the decision, not the domain.
What this site is not
It is not affiliated with TypeSafe, and it is not a mirror of anyone’s posts. Every case links to its original post, keeps only a short excerpt, and rehosts no media and no threads. Where a claim comes from an author we say so and quote their figure as reported rather than verified.
It is also not a tutorial library. The concepts of the model — what the three primitives are, how confidence thresholds work, when not to use it — are already documented well elsewhere, and we link out instead of writing them again.
Start here
If you want to know whether it is worth it, read the benchmark page first and run the scripts from your own region. If you already know what you want to build, start with the case index or the hub closest to your problem: browsers, games and realtime control, or document classification.