---
title: WorldArena
description: "Tsinghua FIB Lab embodied world-model bench: perceptual quality plus data-engine / policy / planner utility."
---

WorldArena (Tsinghua FIB Lab) evaluates embodied world models on two axes. Primary `ewm_score` aggregates the embodied-world-model surface. This catalog id is **`worldarena`**.

- **Perceptual** — visual quality, motion quality, content consistency, physics adherence, 3D accuracy, controllability, human quality.
- **Functional** — utility as a data engine (`data_engine_success`), policy evaluator (`policy_evaluator_correlation`), and action planner (`action_planner_success`).

Paper: [WorldArena](https://arxiv.org/abs/2602.08971). Project: [world-arena.ai](https://world-arena.ai/). Code: [tsinghua-fib-lab/WorldArena](https://github.com/tsinghua-fib-lab/WorldArena).

WorldFoundry **integrates the official video-quality metric runtime** (`runners/worldarena/runtime/video_quality`) and can score one `--dimension` at a time (catalog-bounded example: `action_following`). **One real prepared-data PSNR component is verified. Full Track 1 and the embodied tracks are not.** Functional-utility metrics need embodied task evidence outside the video-quality runtime.

<BenchmarkPageSections id="worldarena" locale="en" />

## How to run

```bash
${WORLDFOUNDRY_UNIFIED_PYTHON} \
  worldfoundry/evaluation/tasks/execution/runners/worldarena/run_worldarena_official_runner.py \
  --run-official \
  --dimension action_following \
  --config-path <worldarena_config.yaml> \
  --generated-artifact-dir <generated_videos> \
  --output-dir tmp/worldarena/official \
  --json
```

Ground-truth comparisons take `--gt-data-dir` / `--action-gt-data-dir`. Weights resolve from `--ckpt-root`. `--official-results-path` imports an existing result file. Env: `WORLDFOUNDRY_WORLDARENA_RESULTS_PATH`, `WORLDFOUNDRY_WORLDARENA_ROOT`. No Hugging Face dataset is required by the contract.

In-tree pointers: `worldfoundry/data/benchmarks/tasks/external/worldarena.yaml`, `worldfoundry/evaluation/tasks/execution/runners/worldarena`.

Outputs include `scorecard.json` (primary `ewm_score`).

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