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| <title>RoboCasa Kitchen Leaderboard — GINIGEN-AI</title> |
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| <h1>🍳 RoboCasa Kitchen Leaderboard</h1> |
| <p class="sub">A neutral, community-maintained leaderboard for Vision-Language-Action (VLA) policies — by <a href="https://huggingface.co/ginigen-ai">GINIGEN-AI</a></p> |
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| <div class="badges"> |
| <a href="https://robocasa.ai"><img alt="RoboCasa" src="https://img.shields.io/badge/Project-RoboCasa.ai-2563eb"></a> |
| <a href="https://arxiv.org/abs/2406.02523"><img alt="RoboCasa paper" src="https://img.shields.io/badge/RoboCasa-arXiv%202406.02523-b31b1b"></a> |
| <a href="https://arxiv.org/abs/2605.03269"><img alt="RLDX-1" src="https://img.shields.io/badge/RLDX--1%20SOTA-arXiv%202605.03269-b31b1b"></a> |
| <a href="https://arxiv.org/abs/2503.14734"><img alt="GR00T" src="https://img.shields.io/badge/GR00T%20N1-arXiv%202503.14734-b31b1b"></a> |
| <a href="https://arxiv.org/abs/2410.24164"><img alt="pi0" src="https://img.shields.io/badge/%CF%800-arXiv%202410.24164-b31b1b"></a> |
| <a href="https://github.com/huggingface/lerobot"><img alt="LeRobot" src="https://img.shields.io/badge/%F0%9F%A4%97-LeRobot-ffd21e"></a> |
| <img alt="license" src="https://img.shields.io/badge/license-MIT-059669"> |
| </div> |
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| <div class="about"> |
| <h2>📖 What is this?</h2> |
| <p><b>RoboCasa Kitchen</b> is a robot-learning benchmark where a single-arm robot (Franka Panda) performs <b>24 atomic kitchen manipulation tasks</b> — picking objects, opening drawers/doors, turning faucets, pressing buttons, and more — inside a photorealistic simulator.</p> |
| <p>This board tracks the <b>average success rate</b> of <b>Vision-Language-Action (VLA)</b> policies: models that take <b>camera images + a natural-language instruction</b> as input and output <b>low-level robot actions</b>. It is the bridge between large multimodal models and real embodied control.</p> |
| <p>RoboCasa has <b>no official leaderboard</b>, and published numbers are scattered across papers under <b>different protocols</b>. GINIGEN-AI aggregates them <b>neutrally</b>, compares within a single <b>matched protocol</b> (the RLDX-1 Technical Report — the most recent head-to-head comparison), and <b>cites every source</b>.</p> |
| </div> |
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| <div class="warn">⚠️ The main table uses the <b>matched protocol</b> from the RLDX-1 report. Entries measured under a different setup (other number of demos / authors' own eval) are listed <b>separately</b> and are <b>not directly comparable</b>. Spotted an error, or want to add your model? Use the submit form below or the Community tab.</div> |
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| <h2 class="sec">🏆 Kitchen 24-task (matched protocol)</h2> |
| <table> |
| <thead><tr><th>#</th><th>Model</th><th>SR (%)</th><th>Org</th><th>Backbone/Arch</th><th>Paper</th><th>Date</th><th>Protocol</th></tr></thead> |
| <tbody> |
| <tr class="top"><td class="rank">1</td><td><b>RLDX-1</b></td><td class="sr">70.6</td><td>RLWRLD / KAIST (Jinwoo Shin)</td><td>MSAT</td><td><a href="https://arxiv.org/abs/2605.03269">arXiv:2605.03269</a></td><td>2026-05</td><td>matched (RLDX-1 report)</td></tr> |
| <tr><td>2</td><td>GR00T N1.6</td><td class="sr">66.2</td><td>NVIDIA</td><td>GR00T</td><td><a href="https://arxiv.org/abs/2503.14734">arXiv:2503.14734</a></td><td>2026</td><td>reproduced in RLDX-1</td></tr> |
| <tr><td>3</td><td>GR00T N1.5</td><td class="sr">65.7</td><td>NVIDIA</td><td>GR00T</td><td><a href="https://arxiv.org/abs/2503.14734">arXiv:2503.14734</a></td><td>2025</td><td>reproduced in RLDX-1</td></tr> |
| <tr><td>4</td><td>π0-FAST</td><td class="sr">63.6</td><td>Physical Intelligence</td><td>π0 (FAST tok.)</td><td>—</td><td>2025</td><td>reproduced in RLDX-1</td></tr> |
| <tr><td>5</td><td>π0</td><td class="sr">62.5</td><td>Physical Intelligence</td><td>π0 (flow)</td><td><a href="https://arxiv.org/abs/2410.24164">arXiv:2410.24164</a></td><td>2024</td><td>reproduced in RLDX-1</td></tr> |
| <tr><td>6</td><td>π0.5</td><td class="sr">62.1</td><td>Physical Intelligence</td><td>π0.5</td><td><a href="https://arxiv.org/abs/2504.16054">arXiv:2504.16054</a></td><td>2025</td><td>reproduced in RLDX-1</td></tr> |
| </tbody></table> |
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| <h2 class="sec">➕ Other protocols (not directly comparable)</h2> |
| <table> |
| <thead><tr><th>Model</th><th>Reported SR (%)</th><th>Org</th><th>Backbone</th><th>Source</th><th>Why separate</th></tr></thead> |
| <tbody> |
| <tr><td>Cosmos-Policy (Predict2-2B)</td><td class="sr">67.1</td><td>NVIDIA</td><td>2B (video-FM finetune)</td><td><a href="https://huggingface.co/nvidia/Cosmos-Policy-RoboCasa-Predict2-2B">model card</a></td><td>50 demos, NVIDIA-own protocol</td></tr> |
| </tbody></table> |
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| <h2 class="sec">🤖 GR1-Tabletop variant (separate suite)</h2> |
| <table> |
| <thead><tr><th>Model</th><th>GR1-Tabletop 24-task SR (%)</th><th>Org</th><th>Source</th></tr></thead> |
| <tbody> |
| <tr><td>GR00T (h=16)</td><td class="sr">59.7</td><td>NVIDIA</td><td><a href="https://arxiv.org/abs/2604.05014">arXiv:2604.05014</a> (StarVLA)</td></tr> |
| <tr><td>TwinBrainVLA</td><td class="sr">54.6</td><td>—</td><td><a href="https://arxiv.org/abs/2601.14133">arXiv:2601.14133</a></td></tr> |
| <tr><td>VP-VLA</td><td class="sr">53.8</td><td>—</td><td><a href="https://arxiv.org/abs/2603.22003">arXiv:2603.22003</a></td></tr> |
| <tr><td>StarVLA-OFT</td><td class="sr">48.8</td><td>—</td><td><a href="https://arxiv.org/abs/2604.05014">arXiv:2604.05014</a></td></tr> |
| <tr><td>GR00T-N1.6</td><td class="sr">24.2</td><td>NVIDIA</td><td>RoboCasa-GR1 (no-collision 7.0%)</td></tr> |
| </tbody></table> |
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| <h2 class="sec">📝 Submit your result</h2> |
| <p class="sub" style="margin:0 0 8px">Submissions are stored privately and reviewed before appearing on the board.</p> |
| <form id="sf"> |
| <div class="row"> |
| <div class="fld"><label>Model name *</label><input name="model" required placeholder="e.g. MyVLA-7B"></div> |
| <div class="fld"><label>Success rate % *</label><input name="sr" type="number" step="0.1" min="0" max="100" required placeholder="e.g. 64.3"></div> |
| </div> |
| <div class="row"> |
| <div class="fld"><label>Protocol *</label><select name="protocol"> |
| <option>Kitchen 24-task (matched)</option> |
| <option>Other protocol</option> |
| <option>GR1-Tabletop</option></select></div> |
| <div class="fld"><label>Paper / URL</label><input name="paper" placeholder="arXiv or HF link"></div> |
| <div class="fld"><label>Your name / org *</label><input name="submitter" required placeholder="e.g. GINIGEN-AI"></div> |
| </div> |
| <button type="submit">Submit</button> |
| <div id="msg"></div> |
| </form> |
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| <div class="foot"> |
| <b>References:</b> |
| <a href="https://arxiv.org/abs/2605.03269">RLDX-1</a> · |
| <a href="https://arxiv.org/abs/2406.02523">RoboCasa</a> · |
| <a href="https://arxiv.org/abs/2603.04356">RoboCasa365</a> · |
| <a href="https://arxiv.org/abs/2503.14734">GR00T N1</a> · |
| <a href="https://arxiv.org/abs/2410.24164">π0</a> · |
| <a href="https://github.com/huggingface/lerobot">LeRobot</a> · |
| <a href="https://robocasa.ai">RoboCasa.ai</a><br> |
| Maintained by <a href="https://huggingface.co/ginigen-ai">GINIGEN-AI</a>. Not affiliated with the RoboCasa authors. Corrections welcome via the Community tab. |
| </div> |
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