UserToolBench: leaderboard

UserToolBench (Sun Yat-sen University and Huawei Noah Ark Lab, 2026) tests whether tool-use LLMs make the decisions a specific user would want when the user profile is hidden: the model sees only the interaction history, the current request and the tool schemas, across 10 privacy-sanitized user profiles and 36 tool sets. Exact trajectory accuracy in percent, averaged over single-tool, multi-tool and lack-of-information tasks; higher is better.

Metric: Exact trajectory accuracy (%; mean of the single-tool, multi-tool and lack-of-information task-type accuracies; a trajectory counts when it matches the profile-conditioned reference: the tool name and decision-relevant arguments, the ordered call sequence for multi-tool tasks, or the correct clarify-or-infer decision when information is missing; 799 profile-hidden evaluation instances from long-horizon interaction trajectories of 10 privacy-sanitized user profiles over 36 tool sets; the model sees the interaction history, the current request and the tool schemas but not the profile). Source: arxiv.org. Saturation forecast: Not forecast. 9 models tracked.

Top models

#ModelScoreOverall rank
1GLM-549.36#260
2DeepSeek V4 Pro42.49#188
3Kimi K2.638.65#178
4Qwen 3.6 Plus37.02#222
5Gemini 3.5 Flash34.32#101
6GPT-5.431.98#123

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

Interactive version: theaggregate.ai/benchmark?slug=usertoolbench · How It Works · Data refreshed daily, snapshot 2026-11-13.