SMH-Bench (Interactive Agent) - Ambiguous Intent: leaderboard

SMH-Bench (2026) category on vague complaints and underspecified requests, where the agent must act sensibly or ask for clarification, scored in the executable HomeEnv smart-home simulator. In the Environment-Interactive Agent setting the model starts with partial observability and must query and control the home through tools in a ReAct loop. The board is the success rate in percent; higher is better.

Metric: Success rate (%) on Ambiguous Intent (TC3, 150 subjective complaints, scene-level goals and slot-missing requests, acting or asking for clarification as appropriate); Environment-Interactive Agent: a ReAct loop that starts from partial observability and queries and controls the HomeEnv simulator through tools under a call budget; final home state checked against the goal with untouched devices preserved; clarification and query answers judged by GPT-5; higher is better. Source: arxiv.org. Saturation forecast: Estimated already saturated. 13 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3.1 Pro (Preview)92#94
2Claude Sonnet 4.691.3#161
3Qwen 3.5 397B A17B86.7#246
4GPT-5.4 Mini86#389
5Claude Haiku 4.585.3#568
6DeepSeek V3.2 (Thinking)85.3#406 (DeepSeek V3.2)
7GPT-5.484.7#123
8GLM-583.3#260
9Qwen 3.5 Plus76.7#232
10Qwen 3.5 4B72#1175
11Qwen 3.5 9B69.3#803
12MiniMax-M2.752#518

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

Interactive version: theaggregate.ai/benchmark?slug=smh-bench-interactive-agent-ambiguous-intent · How It Works · Data refreshed daily, snapshot 2026-11-13.