devwithjev
— reading now— views
Submit a build

Jev-Style Models Control Doom

Nishaanth Reddy gave four Jev-style decision models controls to Doom: Jev, Laya, finetuned ModernCE, and Qwen3.5. A deterministic Python adapter turns ViZDoom’s visible-object labels and HUD into text, and each model chooses whether to turn, move, or fire.

Nishaanth Reddy@reddmachine𝕏
I gave four Jev-style decision models the controls to Doom: Jev, Laya, finetuned ModernCE and Qwen3.5. A deterministic Python adapter turns ViZDoom's visible-object labels + HUD into text. Each model picks turn, move or fire. No extra Doom-specific training. Same starting seed, separately recorded games. Each model's actions change its view. The video shows action probabilities, kills and survival
Sep 19, 2026X postsView on X
The models play from the same starting seed in separately recorded games. Each model’s actions change its view; the video shows action probabilities, kills, and survival.

Also filed under Games & real time

  • Benchmarks Jev on Pokémon Red

    The project benchmarks Jev, TypeSafe’s fast decision model, against Jev paired with a GPT-6 Sol planner for playing Pokémon Red.

  • Plain-English Cellular Ecosystem Simulator

    LifePot is a cellular automaton-inspired ecosystem that users describe in plain English. Jev turns those inputs into species, feeding relationships, reproduction strategies, and environmental conditions.

  • Mapping Children's Behavioral Intent in Games

    Mores Research used Jev to map children’s behavioral intent in games and examine how it correlates with real-world behavior. It reports mapping intents across 45+ real sessions involving 20 child users over a long horizon.

  • StarCraft Agent for Fast Tactical Decisions

    Jev_Star is a StarCraft agent experiment that uses Jev for fast tactical decisions.