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Jevman vs LLM Fuzz CI

Ambos están en Woodander. Esto es lo que hace cada uno, para quién es y en qué se diferencian — según lo que escribieron sus creadores y nuestros editores.

Jevman LLM Fuzz CI
Qué es Seven AI decision models played Pac-Man in real time against the classic arcade ghosts. See the leaderboard, watch their games, or play against them. A GitHub Action that lets a coding agent write adversarial inputs for your tests, and reports only the ones that fail.
Categoría Apps y asistentes de IA Apps y asistentes de IA
Precios — —
Página mantenida por Editores de Woodander Editores de Woodander
En Woodander desde octubre 2026 octubre 2026
Sitio web opper.ai tiime-software.github.io

Sobre Jevman

Seven AI decision models played Pac-Man in real time against the classic arcade ghosts. See the leaderboard, watch their games, or play against them. Openai just launched their decisions endpoint, cloudflare launched clef the other week, and many more jev alternatives are out there.We wanted to put the popular ones to the test and thought Pac-Man is a good benchmark for simple and fast decision making.So we let jev 1.13, kev, clef, clef flash, GPT-6 Luna and Laya play Pac-Man against bot ghosts.The low latency of these models allows for real time play. We had each model play 100 games, published a leader board and open-sourced the repo so anyone can run their own model and join the ranking. Link to repo: https://github.com/op...

Elige Jevman si necesitas seven AI decision models played Pac-Man in real time against the classic arcade ghosts. See the leaderboard, watch their games, or play against them.

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Sobre LLM Fuzz CI

A GitHub Action that lets a coding agent write adversarial inputs for your tests, and reports only the ones that fail. Hi HN!Most of the explanation is in the blog post, and the code lives there: https://github.com/tiime-software/llm-fuzz-ci/Happy to receive feedback, and to know how other people use agents to improve code security!

Elige LLM Fuzz CI si necesitas a GitHub Action that lets a coding agent write adversarial inputs for your tests, and reports only the ones that fail.

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