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
Jev Wikiracer
A Wikipedia race you play against Jev. From the same start article, each hop is one Choice over that page's outbound links.
- Category
- Demos & Experiments
- Format
- Playground
- Published by
- Community
- Author
- —
- Added
- 2026-09-28
- Last verified
- 2026-09-28
Highlights
- You and Jev start on one Wikipedia article and race to a target using only in-article links.
- Each Jev hop is one Choice over dozens of outbound links, asking which link gets closest to the target.
- The page says the hosted race needs no key, and quotes about 200 ms per hop.
- A random-pair button picks the start and target. First to the target wins.
Watch out
Independent site, not TypeSafe or Wikimedia. The sample client posts to jevtypesafeai.com/api/v1/decide. Link text is whatever Wikipedia returns.
Reactions & coverage
Posts, threads, and videos about this entry from around the web.
Hacker News: Show HN: a mouse colony where each next move is Jev or a fixed rule.
1 pointShow HN: Jev-mice – mouse colony simulation using Jev and deterministic engineRead the thread on Hacker NewsHacker News: Show HN: OpenDecision, a local decision model with a Doom demo.
dwa35926 pointsShow HN: OpenDecision – a 400M zero-shot model makes local decisions, plays DoomRead the thread on Hacker NewsX: Jev plus Astra beats the Ender Dragon for under a dollar
X: Jev plays Pokémon Showdown
1/8 Saw Jev from @typesafeai on my feed, so I made it play Pokemon Showdown. Codex built the harness. It was damn fast. Its choices were a mixed bag. Full match, video 1/2. This is a saved replay with decision data, latency and added reading pauses.
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Jevの内部アーキテクチャを推測している技術記事(Jev’s Architecture Unmasked)からメモ。 ・本記事はJevのAPIを約1万回の呼び出して、内部構造を推測したもの ・従来の言語モデルを用いた分類やルーティングでは、トークンを1文字ずつ逐次生成するために膨大な無駄な計算コストが発生していた。 Show more
The open System One roundup
Jev 发布没几天,开源社区已经开始疯狂复刻了🔥 最值得推荐的五个模型: 1、Laya 421M:原生决策模型,支持 Mac 2、Decider-2B:最像 Jev,基于 Qwen3.5 3、NanoJev 0.6B:专门的 Decision Head 4、Reflex:Qwen3.5 + Direct Logits 5、System-One 4B:专门做概率校准 Show more
Jev 刚发布没几天,开源社区就出现了同款🔥 Decider-2B模型,是基于 Qwen3.5-2B 做了特殊调整 它和 Jev 模型是一样的 只做选择 评分和判断 不是文本类的 LLM 模型 但两者还是有几个明显区别: 1、模型 Jev:闭源 System One Model Decider:Qwen3.5-2B,约 1.9B 参数,Apache 2.0 开源 2、价格
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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




