№ 0085Reddit post
DungeonBench: LLMs navigating a grid dungeon
Open-source benchmark where models navigate a 10x10 dungeon in order; Muse-Glimmer-30B (medium) scored 10/12 with 2 illegal moves.
u/Cradawx built DungeonBench (github.com/shinomakoi/dungeon-bench), which has LLMs navigate a 10x10 grid, collect a weapon, kill a monster and exit, failing after three illegal moves. Muse-Glimmer-30B at medium reasoning scored 10/12, described as efficient and confident but sometimes overconfident, skipping objectives.
DungeonBench - testing LLMs at simple games
LLMs have become extremely good at coding, maths etc, but how well do they do at playing a simple dungeon/maze game that even a child can solve easily? The LLM has to navigate a 10x10 grid map, completing objectives in the right order (collect weapon > kill monster > head to exit) while navigating the dungeon and avoiding walls. Three illegal moves fail the run. All models are tested with reasoning enabled. The code and more info on my GitHub if you want try it yourself: https://github.com/shinomakoi/dungeon-bench Model leaderboard: Model Score DeepSeek-V4-Pro (high) 🥇12/12 Gemma-4-31B-it 🥈11/12 Qwen-3.8-27B (medium) 🥈11/12 GLM-5.3-Flash (high) 🥈11/12 Muse-Glimmer-30B (medium) 🥉10/12 DeepSeek-V4-Flash (high) 🥉10/12 Granite 4.2 (full) 8/12 KAT-Coder-V2.5-Dev 8/12 Nemotron-3.5-Lightning-30B-A3B 5/12 Model Illegal moves DeepSeek-V4-Pro (high) 🥇0 Gemma-4-31B-it 🥈1 Qwen-3.8-27B (medium) 🥈1 Muse-Glimmer-30B (medium) 🥉2 Granite 4.2 (full) 🥉2 Nemotron-3.5-Lightning-30B-A3B 7 GLM-5.3-Flash (high) 8 KAT-Coder-V2.5-Dev 10 DeepSeek-V4-Flash (high) 12 DeepSeek-V4-Pro: By far the best result. Basically perfect performance in all maps.
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