TravelEval - Attraction Quality Efficiency: leaderboard
TravelEval (KDD 2026) asks an LLM for a complete multi-day travel plan and simulates it in a sandbox of 10 Chinese cities with real transport, hotel and attraction data. Scores are from Direct prompting over 1,150 queries. The board measures whether visit time goes to highly rated attractions (score weighted by time), in unbounded paper units; higher is better.
Metric: Attractions Quality Efficiency (AQE): attraction score weighted by effective visit time, over total visit time (paper units, unbounded); Direct prompting (one pass, no tools), plans simulated in the TravelEval sandbox of 10 Chinese cities (real rail, flight, hotel and attraction data, queuing-time model, road-network distances) over 1,150 queries; higher is better. Source: arxiv.org. Saturation forecast: Around December 2026. 7 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Claude Sonnet 4.5 | 1.03 | #250 |
| 2 | Gemini 2.0 Flash | 1.01 | #704 |
| 3 | DeepSeek V3.1 (Non-reasoning) | 0.99 | #497 (DeepSeek V3.1) |
| 4 | GPT-5 Chat | 0.84 | #444 |
| 5 | GPT-4o (2024-11-20) | 0.73 | #866 |
| 6 | GPT-4o Mini (2024-07-18) | 0.71 | #1510 |
| 7 | Qwen 3 8B | 0.68 | #1830 |
No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.
Interactive version: theaggregate.ai/benchmark?slug=traveleval-attraction-quality-efficiency · How It Works · Data refreshed daily, snapshot 2026-11-13.