---
title: Meta-World
description: "CoRL 2019 Sawyer / MuJoCo suite: 50 skills, MT and ML splits. WorldFoundry imports official result exports — it does not run MuJoCo."
---

Meta-World (CoRL 2019) is Stanford, UC Berkeley, and USC's multi-task and **meta-RL** manipulation benchmark, now maintained by the **Farama Foundation**. A **Sawyer** arm in **MuJoCo** must solve **50** distinct tabletop skills (reach, push, drawer, assembly, …). Official evaluation is **not** one number: you name the suite.

Multi-task (same policy, shared training):

- **MT1** — one skill.
- **MT10** — ten skills; report mean success.
- **MT50** — all fifty.

Meta-learning (adapt to held-out tasks / goals):

- **ML1** — one skill, held-out goals.
- **ML10** — 10 meta-train / 5 meta-test skills.
- **ML45** — 45 meta-train / 5 meta-test skills.

The usual report card is **binary success rate**, not raw return. Paper: [Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning](https://arxiv.org/abs/1910.10897). Project: [meta-world.github.io](https://meta-world.github.io/). Code: [Farama-Foundation/Metaworld](https://github.com/Farama-Foundation/Metaworld) (MIT).

WorldFoundry is **official-results only**. You run Farama Metaworld / MuJoCo upstream, then `official-validation` normalizes JSON/CSV. No in-tree simulator. Declare the MT/ML suite with the export or the rows cannot be compared.

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

## How to run

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

Default import path when you omit `--official-results-path` is `WORLDFOUNDRY_METAWORLD_RESULTS_PATH`. Manifest: `worldfoundry/data/benchmarks/tasks/external/metaworld.yaml`. Outputs: `scorecard.json` (primary `success_rate`) and `raw_results.jsonl`.

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