AsyncPlan Online Robo Challenge (Planner): leaderboard
Online Robo Challenge from Robust Asynchronous Planning via Auto-Formalization (Zhang et al., 2026): the 140 Robotouille-based kitchen tasks with execution-time events such as new deliveries, deadlines and resource changes, so completed and running actions must be preserved while the rest is replanned. Here the LLM writes the schedule directly, zero-shot at temperature 0; plan accuracy in percent, higher is better.
Metric: Plan accuracy (%; share of the 140 Online Robo Challenge episodes of the kitchen tasks (seven splits of 20 built on Robotouille, with object states, resources, stations and multiple agents) whose plan is valid and reaches the optimal makespan; execution-time events (new deliveries, deadlines, resource changes) require replanning or one-shot re-formalization; the LLM writes the schedule directly (Planner); zero-shot, temperature 0). Source: arxiv.org. Saturation forecast: Around 2029. 4 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | GPT-5 Mini | 35 | #349 |
| 2 | Qwen 3.6 35B A3B | 30.7 | #461 |
| 3 | Gemini 3 Flash | 17.1 | #159 |
| 4 | DeepSeek V4 Flash | 12.9 | #254 |
No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.
Interactive version: theaggregate.ai/benchmark?slug=asyncplan-online-robo-challenge-planner · How It Works · Data refreshed daily, snapshot 2026-11-12.