Yunncheng/gamewam-models

GameWAM Models

GameWAM models for closed-loop game control: world action models built on Wan2.2-TI2V-5B that jointly model video prediction and native actions, and act online with block-cycle control (predict 16 steps, commit 8).

• Paper: arXiv:2608.26200
• Code: yunncheng/GameWAM
• Training data: gamewam-minecraft, gamewam-vizdoom

Repository contents

Directory	Game	Task config	Checkpoint
minecraft/	Minecraft	mc_uncond_ar_224_4e-5	gamewam-minecraft.pt (12.2 GB)
vizdoom/	ViZDoom	vizdoom_uncond_ar_224_2e-4	gamewam-vizdoom.pt (12.2 GB)

Each subdirectory holds one checkpoint and its paired dataset_stats.json. Always load a checkpoint together with the dataset_stats.json from the same subdirectory.

Minecraft model

Base	Wan2.2-TI2V-5B (video expert, 5.0B params) + ActionDiT action expert (1.0B params)
Task config	mc_uncond_ar_224_4e-5
Training	LR 4e-5, 21,900 steps, BF16, DeepSpeed ZeRO-2, 8xH200
Proprio input	15-D canonical state + 6-D field validity
Action space	22-D keyboard/mouse, route-aware normalization, GUI head enabled
Control	prediction_horizon=16, execution_horizon=8 (block-cycle)
Precision	bfloat16

hf download yunncheng/gamewam-models --include "minecraft/*" --local-dir gamewam-models

bash scripts/eval_mc_multi.sh --mode all --episodes 5 \
    --ckpt gamewam-models/minecraft/gamewam-minecraft.pt \
    --dataset_stats gamewam-models/minecraft/dataset_stats.json \
    --output evaluate_results/minecraft/gamewam-release

The default mc_uncond_ar_224_4e-5 task configuration matches this checkpoint.

ViZDoom model

Base	Wan2.2-TI2V-5B (video expert, 5.0B params) + ActionDiT action expert (1.0B params)
Task config	vizdoom_uncond_ar_224_2e-4
Training	LR 2e-4, 28,000 steps, bfloat16
Proprio input	4-D game state (POSITION_X, POSITION_Y, ANGLE, HEALTH)
Action space	9-D (shoot, movement, strafe, speed, turn; turn_delta continuous)
Control	prediction_horizon=16, execution_horizon=8 (block-cycle)
Precision	bfloat16

hf download yunncheng/gamewam-models --include "vizdoom/*" --local-dir gamewam-models

bash scripts/eval_vizdoom_multi.sh --mode all --episodes 50 \
    --ckpt gamewam-models/vizdoom/gamewam-vizdoom.pt \
    --dataset_stats gamewam-models/vizdoom/dataset_stats.json \
    --output evaluate_results/vizdoom/gamewam-release

The default vizdoom_uncond_ar_224_2e-4 task configuration matches this checkpoint.

See the repository README for installation, data preparation, and the full evaluation protocol.

Citation

@misc{guo2026gamewamworldactionmodel,
      title={GameWAM: A World Action Model for Video Games},
      author={Yuncheng Guo and Zhanqiu Zhang and Yiwen Guo and Weijia Li},
      year={2026},
      eprint={2608.26200},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/2608.26200},
}