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Jev plays Pac-Man

An autonomous Pac-Man recreation steered by Jev: before each junction the game sends the maze, actors, and legal directions as structured data, and Jev returns one direction with a probability per option.

Category
Cookbooks & Demos
Format
Playground
Published by
Community
Author
—
Added
2026-09-25
Last verified
2026-09-25

Highlights

  • No screenshots and no hidden pathfinding: the maze goes to Jev as structured text.
  • The game runs at half speed and keeps moving while Jev answers, targeting junctions far enough ahead.
  • The HUD tracks score, lives, level, and pellets left, with a manual mode and 0.25x to 1x speeds.

Watch out

The page credits no author or repository and publishes no latency or cost measurements.

Reactions & coverage

Posts, threads, and videos about this entry from around the web.

X: Jev plus Astra beats the Ender Dragon for under a dollar

X: Jev plays Pokémon Showdown

X: Jev plays Puyo Puyo with real-time board questions

X: Jev plays Smash Bros. against itself

Related terms

Glossary definitions related to this entry.

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From the community

Posts from builders shipping with Jev right now.

Follow @typesafeai

Foreman keeps coding agents on task

Unclutter: an ad and slop blocker that runs on Jev

An open-source BS meter for debates and investor calls

🚨 Open Source Jev BS meter you can use this to analyze any debate / investor call / interview / sales pitch / podcast video fact check live , for example this dario interview cost 60 Jev calls / 111K tokens / $0.0047 github.com/ChetasLua/jevm…

Chetaslua
Chetaslua
@chetaslua

🚨 I gave the Trump vs Kamala debate a live BS meter using Jev every sentence, both candidates, 5 yes/no questions each 1,191 Jev calls / 1.18M tokens / 415 ms median total cost : $0.0497 same questions for both, clips picked by one fixed rule, not a fact-check

Reply

A Jev-shaped model on Cerebras and Qwen

Built an alternative version of @typesafeai but on @cerebras with Qwen 3.8 27b. Similar quality, similar performance, but vastly different cost. TypeSafe was way cheaper, and did beat Qwen on performance. Closest we can get using LLMs I think. Source: github.com/iammrduncan/ty…

Diogo Almeida
Diogo Almeida
TypeSafe AI
@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

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Jev benchmarked on two public safety corpora

1/ Benchmarked TypeSafe's Jev on two public safety corpora. It doesn't generate text, it returns calibrated probabilities you threshold in code. 96.5% on prompt injection, all 662 messages in deepset/prompt-injections. No tuning. 325ms p50.

Terminal dashboard showing 96.5% accuracy on prompt injection and 89.0% pairwise on vulnerable code, with a context ablation and calibration plot.
Diogo Almeida
Diogo Almeida
TypeSafe AI
@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

Reply

An open 151M-parameter decision engine

TypeSafe AI came out of stealth with Jev, and access is behind a waitlist. I built an open source version Verdict (Open-jev) you can run right now in a browser tab: And its a real post trained model..(link in comments) It is a post trained 151M parameters model. ModernBERT-base Show more

Image
Diogo Almeida
Diogo Almeida
TypeSafe AI
@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

Reply