Skip to content

The full directory

All Jev AI model resources

Entries for TypeSafe AI's flagship System One model — official docs and SDKs alongside community clients, tools, and write-ups.

Entries
3,739
Categories
11
Official
102
Community
3,637
Source sites
292
Deep dives
3,739

By format

3739
  • Docs169
  • Repos & sites2980
  • Videos73
  • Posts103
  • Articles344
  • Playgrounds70

Updated

Browse the Jev AI model by category

11 ways into the ecosystem. Each category page leads with its own shortlist of starting points.

All 3739 Jev AI model resources

Search the full directory, or filter by category and tag.

Showing 14 of 3739 resources

Per WSJ's search excerpt, the three-week-old Jev has set Silicon Valley abuzz with talk of alternatives to large language models and is already sparking copycats. It classifies inputs to predetermined outputs: yes or no, a numerical score, or answers on a list.
Jev Media & TalksArticle#community#press#competition
Community
Fortune reports Jev went viral among developers, with nearly 13% of Vercel's paid teams trying it within a day of its gateway arrival. Three weeks after Jev's launch, OpenAI rolled out a competing Decisions API built on GPT-6 Luna.
Jev Media & TalksArticle#community#press#competition
Community
Bloomberg News reports Jev went viral with the promise of a cheaper, faster alternative to large language models, its launch video nearing 40 million views on X. Per the Financial Times, investors have offered funding valuing TypeSafe AI above $10 billion.
Jev Media & TalksArticle#community#press#funding
Community
INXEN's syndication of Financial Times reporting says TypeSafe, last valued at $200 million, is fielding offers that would value it at $10 billion or more days after launching Jev, with Vercel citing record paid-developer interest.
Jev Media & TalksArticle#community#press#funding
Community
A community roundup of every public Jev evaluation: TypeSafe's own workflow evals plus at least twenty independent builder benchmarks. The site reports speed medians of 127-422 ms per call leading every LLM compared, while accuracy splits by task.
Jev Media & TalksArticle#community#press#calibration
Community
Blackwell Systems' adversarial technical due diligence on Jev, built only from public material and live API calls. The author reproduces TypeSafe's published addressee numbers within a point and finds a real but noise-type-specific robustness moat.
Jev Guides & ArticlesArticle#community#press#competition
Community
An independent hands-on evaluation that ran Jev live on 16,379 benchmark requests and reports it is no frontier model but genuinely useful for cheap real-time sub-frontier judgement, with 82.7% MMLU-Pro and 76.5% GPQA Diamond.
Jev Guides & ArticlesArticle#community#press#competition
Community
A playground operator's audit of every published Jev number: TypeSafe's four-workflow evals, the favourable homepage demo, independent tests and its own calls. It concludes the price and speed are real and the intelligence claim is roughly mid-tier frontier on decision workflows.
Jev Media & TalksArticle#community#press#explainer
Community
Celeris's launch post for Celeris-1-decision, a hosted diffusion language model for typed decisions. It reports 80.0% on the full jev-bench, the lowest Brier scores of five decision APIs tested, a 67 ms median and $0.04 per million input tokens.
Jev Media & TalksArticle#community#press#competition
Community
AICrier's news-feed summary of Celeris-1 Decision: a multimodal diffusion model for bounded structured decisions that Celeris says reaches 80% on JevBench, 7 points above Jev 1.13.0, with 67 ms median latency.
Jev Media & TalksArticle#community#press#competition
Community
Interactive comparison of 21 decision models, with direct-provider and OpenRouter routes measured separately on 1,100 public jev-bench items. The charts plot accuracy against benchmark cost, official prices and median latency, with Jev 1.13 and 1.14 measured separately.
Jev Guides & ArticlesArticle#community#press#calibration
Community
Doug Does' benchmark dashboard for JevBench: 534 questions, 48 ranked models, composite scores that already include cost, head-to-head comparison, latency and a Pareto frontier. Jev 1.13.0 tops the table at 74.40.
Jev Media & TalksArticle#community#press#competition
Community
The desk's index of every Jev measurement it has published, keeping each figure's original caveat: JevBench boards, Vercel gateway reach, Celeris and Artificial Analysis results, and the desk's own Jev Day probes which it says it did not rerun.
Jev Guides & ArticlesArticle#community#press#calibration
Community
Side-by-side tables placing similar Jev tests next to each other, from the JevBench API board to Vercel paid-team reach, with the desk's warning that differing sets, labels and comparators mean the rows are not a ranking.
Jev Guides & ArticlesArticle#community#press#competition
Community

Start here with the Jev AI model

Hand-picked entries the maintainers recommend first, from official primitives to community tools.

The Jev Day release post: Jev 1.14.0 under jev-preview plus three danger-zone features — composable images on both models, the box question type on 1.14 only, and opt-in 262k context.
Jev Guides & ArticlesArticle#official#release#vision
Official
The box question type: one bounding box per question, returned as four edges that are fractions of the image, plus confidence, with no criteria field and no not-found value.
Jev Practices & PatternsDocs#official#docs#vision
Official
LiteLLM's Day 0 post for TypeSafe Jev 1.14: the proxy adds box questions, image input and long-context mode on both POST /v1/systemone and POST /v1/decisions, forwarding TypeSafe-Danger-Zone headers only to TypeSafe deployments.
Jev Integrations & AdaptersArticle#community#litellm#gateway
Community

From the Jev community

Watch walkthroughs, read the threads, and see what builders are posting.

YouTube: KodeKloud's three-minute primer: what a System One model decides, and why it answers in milliseconds.

YouTube: Caleb Writes Code explains what Jev is and how to call it, in seven minutes.

YouTube: Greg Isenberg and Ryan Vogel on the businesses Jev unlocks, and a path in through the Vercel AI Gateway.

YouTube: CJ from Syntax demos browser use, classification, code review, a model router, and a chat bot with no LLM.

YouTube: Ryan Vogel runs Jev on 100 and then 1,000 emails: category, priority, spam, and reply predictions.

YouTube: AICodeKing tests support routing, refund detection, prompt-injection resistance, and browser automation.

Hacker News: Show HN: Ad Spend Guard gates budget before the auction, not the creative after.

Show HN: Gating ad budget with a decision modelRead the thread on Hacker News

Reddit: Reranking rebooking options with a decision model, ranked with reasons.

Hacker News: Pick Verify: a single decision at the warehouse pick station catches confusable picks.

Show HN: Verifying robot picks with a decision modelRead the thread on Hacker News

Hacker News: Software Bombe and live Enigma demo where Jev ranks cribs and judges plaintext.

ag_212 pointsShow HN: Jev as the Bletchley Park Analyst: A Software Bombe on EnigmaRead the thread on Hacker News

Hacker News: Show HN for the decide CLI: brew install, file context, and multi-question shell scripts.

vsekhar2 pointsShow HN: Decide – Jev decisions in the shell, scripts, and agent skillsRead the thread on Hacker News

How entries are chosen

Every entry is reviewed against the same bar, whether it comes from TypeSafe or the community.

  • Public and working — no paywalls, sign-up walls, or dead links.
  • Concrete — it has to be about Jev and the System One API, not generic LLM content.
  • Useful today — something a developer can learn from or use right now.
  • Distinct — if a similar entry exists, the description has to say what makes this one different: a different runtime, a cheaper path, a measured result, or a narrower focus.
  • Documented — repos state their license, and docs are in English or carry an English summary.

Spam, affiliate links, and thin AI-generated content are rejected. New entries are expected to ship with a deep dive: two to five highlights, caveats, a quickstart snippet where one helps, and a verification date. Star counts are refreshed when an entry is touched.

Common questions

Short answers about Jev and how this directory works.

What is the Jev AI model?

Jev is TypeSafe AI's first System One model — an AI model that takes a state plus typed questions and returns one structured answer per question: a choice, an ordered score, or the probability of yes, with calibrated confidence on Choice and Score answers. Code can branch on the result without parsing generated text.

What is the difference between Choice, Score, and Noul?

They are the three question primitives. Choice picks one of up to 255 options, Score rates on 2 to 10 ordered levels, and Noul answers yes or no. Choice and Score answers carry a confidence between 0 and 1; a Noul answer is the probability of yes.

Which Jev SDKs and client libraries are available?

TypeSafe maintains official JavaScript/TypeScript and Python SDKs plus a Python adapter. The community has built clients for Go, .NET, PHP, Laravel, Rust, Elixir, Ruby, and Scala, along with framework integrations such as DSPy, LlamaIndex, and Home Assistant. All of them are listed in the Repos & SDKs category.

Is the directory free, and is it affiliated with TypeSafe AI?

The directory is free to browse: every entry is reviewed, and spam, affiliate links, and sign-up walls are rejected. JevDirectory.org is community-run and not affiliated with TypeSafe AI — Jev and System One are TypeSafe AI trademarks.

How often is the directory updated?

Entries are added as new resources appear and re-checked when they are touched. The directory currently holds 3739 entries from 292 source sites, last updated Oct 25, 2026.

What is a verified deep dive?

Most entries include a deep dive: two to five highlight bullets someone would only know from using the resource, a caveats note about limits and requirements, an optional quickstart snippet, and the date the link was last checked. 3739 of the 3739 entries carry one today.

For the canonical details, read the official TypeSafe docs and the API reference.