AppWorld-UL (Function Calling) - Infeasible Tasks: leaderboard
AppWorld-UL (2026) turns AppWorld test-challenge scenarios into user-in-the-loop tasks that are infeasible, underspecified or need confirmation, so an agent succeeds only if it also asks, informs or confirms with a simulated user. Interactive task goal completion in percent on the 102 infeasible tasks with a function-calling agent; higher is better.
Metric: Interactive task goal completion (%; share of 102 tasks made infeasible, where the agent must tell the user whose AppWorld unit tests all pass, including a test that the agent asked the simulated user for every piece of hidden information it needed; function-calling agent over the AppWorld app APIs; GPT-5.5 user simulator answering from a fixed knowledge set). Source: arxiv.org. Saturation forecast: Not forecast. 5 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | DeepSeek V4 Pro | 33.3 | #188 |
| 2 | Kimi K2.6 | 32.4 | #178 |
| 3 | Qwen 3.7 Max | 28.4 | #145 |
| 4 | GPT-5.5 (Medium) | 28.4 | #49 (GPT-5.5) |
| 5 | Claude Opus 4.7 | 25.5 | #79 |
No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.
Interactive version: theaggregate.ai/benchmark?slug=appworld-ul-function-calling-infeasible-tasks · How It Works · Data refreshed daily, snapshot 2026-11-13.