PersonaTrail (ReasoningBank) - Single-hop Preference Inference: leaderboard

PersonaTrail (2026) evaluates personalized web agents on live websites that must resolve under-specified requests from a raw browsing history, run through the Browser-Use agent framework. Task success in percent on single-hop preference inference (infer a missing preference from recurring behaviour), with history supplied through ReasoningBank reasoning memory; higher is better.

Metric: Task success rate (%; single-hop preference inference: an under-specified query whose missing preference must be inferred from recurring browsing behaviour; success needs the right website, the task intent and the preference all satisfied; live websites through a Browser-Use web agent with at most 30 steps and temperature 0, given memory from ReasoningBank (per-user reasoning items distilled from successful and failed trajectories); Gemini 3.1 Pro evaluator; the three proprietary backbones run on a 25% stratified subset). Source: arxiv.org. Saturation forecast: Around February 2027. 6 models tracked.

Top models

#ModelScoreOverall rank
1Claude Haiku 4.555.69#568
2Gemini 3 Flash46.88#164
3Qwen 3.6 27B46.45#341
4GPT-5.4 Mini25.98#389
5Gemma 3 27B (IT)25.66#1289
6Llama 4 Scout16.67#1776

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=personatrail-reasoningbank-single-hop-preference-inference · How It Works · Data refreshed daily, snapshot 2026-11-13.