File size: 3,403 Bytes
714be82 28856d9 714be82 28856d9 3fe5966 28856d9 3f017fd 28856d9 087f583 28856d9 1df754b 28856d9 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 | ---
license: other
license_name: minimax-h3-community-license
license_link: https://huggingface.co/MiniMaxAI/MiniMax-H3/blob/main/LICENSE
base_model: MiniMaxAI/MiniMax-H3
pipeline_tag: video-to-video
tags:
- lora
- video-to-video
- game-rendering
- minimax-h3
---
# AnyGameRenderer: Entity-Consistent Generative Rendering Across Games and an Entity-Level Benchmark
AnyGameRenderer takes a crude gameplay recording (the "programmer art" agents produce: gray boxes and colored cylinders on flat ground) and a text prompt, and outputs the same gameplay re-rendered in the prompted style, frame-aligned with the input.
This repository holds the **LoRA** (`anygamerenderer_lora.safetensors`, 2.4 GB) that turns [MiniMax-H3](https://huggingface.co/MiniMaxAI/MiniMax-H3) Ref2VA into AnyGameRenderer. Paper: https://arxiv.org/pdf/2610.31466 · Project page: https://alaya-lab.github.io/AnyGameRenderer/ · Inference code, the caption builder, and examples: https://github.com/AlayaLab/AnyGameRenderer.
- 🎮 **Generalizes across genres:** one checkpoint renders tower defense, auto-battlers, top-down survivors, turn-based battles, kart racing, crowd runners, arena survival, co-op games, and shooters.
- 🎯 **Keeps entity correspondence:** group counts stay correct, entities appear and disappear on the right frame, and small far-away entities are not lost.
- 📹 **Its input is plain video:** gray blockouts, colored primitives, semantic maps, wireframes, and coarse mockups all work, with no per-object labels or engine hooks.
- 🎨 **Any prompted style:** photoreal AAA, LEGO, Ghibli, crayon, synthwave, samurai, candy land … with the characters re-imagined to match.
## Files
| file | size | what |
|---|---|---|
| `anygamerenderer_lora.safetensors` | 2.4 GB | LoRA on the MiniMax-H3 Ref2VA transformer: rank 128, alpha 128, on `attn.qkv_proj`, `attn.out_proj`, `mlp.fc1`, `mlp.fc2` of every block (musubi-tuner `networks.lora_minimax_h3` format). |
The base weights (Ref2VA transformer, Qwen3-VL-32B text encoder, video and audio VAEs, ~123 GB) are not included; download them from [Comfy-Org/MiniMax-H3](https://huggingface.co/Comfy-Org/MiniMax-H3) after accepting the MiniMax-H3 Community License.
## Usage
```bash
git clone https://github.com/AlayaLab/AnyGameRenderer.git && cd AnyGameRenderer
bash setup_env.sh && conda activate agr
bash download_weights.sh # base weights -> weights/
huggingface-cli download AlayaLab/AnyGameRenderer anygamerenderer_lora.safetensors --local-dir weights
bash run_example.sh # renders the bundled examples (~17 min per 5 s clip on an 80 GB GPU)
```
Inputs are 1344×768, 24 fps clips of 2–15 s; captions are built from a short `spec.json` with `make_caption.py` (see the repo README and the `anygamerenderer-caption` skill for how to write one).
## Citation
```bibtex
@article{liu2026anygamerenderer,
title={AnyGameRenderer: Entity-Consistent Generative Rendering Across Games and an Entity-Level Benchmark},
author={Liu, Ruicong and Ouyang, Liangyang and Lan, Fengbo and Wang, Zhixiang and Zhang, Kaipeng},
journal={arXiv preprint arXiv:2610.31466},
year={2026}
}
```
## License
The LoRA is a derivative of the MiniMax-H3 weights and is distributed under the [MiniMax-H3 Community License](https://huggingface.co/MiniMaxAI/MiniMax-H3/blob/main/LICENSE).
|