---
title: RoboCasa
description: "UT Austin & NVIDIA kitchen simulation — 120 scenes, 100+ atomic and composite tasks. WorldFoundry imports official rollouts."
---

RoboCasa is UT Austin and NVIDIA's large-scale **kitchen** simulation for generalist robots: **120** realistic kitchen layouts, **2,500+** 3D assets (many generated), and about **100** atomic skills plus **composite** long-horizon activities, with large demonstration sets. The paper is [RoboCasa: Large-Scale Simulation of Everyday Tasks for Generalist Robots](https://arxiv.org/abs/2406.02523). Project: [robocasa.ai](https://robocasa.ai/). Code: [robocasa/robocasa](https://github.com/robocasa/robocasa). GitHub license metadata in this catalog is `other:noassertion_github_api` — read the upstream terms before reuse.

WorldFoundry **imports** official rollout exports. Scene assets and long-horizon policy execution stay upstream. Repo mirror: `cache/vla_va_wam/repos/robocasa--robocasa`. Models such as [Being-H0.5](/docs/guides/supported-models/being-h05) publish a RoboCasa specialist line; that is not a score on this page.

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

## How to run

```bash
worldfoundry-eval zoo benchmark-run \
  --benchmark-id robocasa \
  --mode official-validation \
  --official-results-path <official_results.json> \
  --output-dir tmp/robocasa/official-validation \
  --json
```

Default import path: `WORLDFOUNDRY_ROBOCASA_RESULTS_PATH`. Manifest: `worldfoundry/data/benchmarks/tasks/external/robocasa.yaml`. Declare atomic vs composite (and the scene split) with the export. Outputs: `scorecard.json` (primary `success_rate`) and `raw_results.jsonl`.

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