TravelEval - Cuisine Preference: 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 is the percentage of plans that honour the requested cuisine; higher is better.

Metric: Preference Achievement Sign for cuisine (PAS-C): plans honouring the requested cuisine (% of plans); 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 February 2027. 7 models tracked.

Top models

#ModelScoreOverall rank
1DeepSeek V3.1 (Non-reasoning)83.54#497 (DeepSeek V3.1)
2Claude Sonnet 4.579.91#250
3Gemini 2.0 Flash77.56#704
4GPT-5 Chat69.35#444
5GPT-4o (2024-11-20)67.3#866
6GPT-4o Mini (2024-07-18)60.67#1510
7Qwen 3 8B59.96#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-cuisine-preference · How It Works · Data refreshed daily, snapshot 2026-11-13.