SMH-Bench (Interactive Agent): leaderboard

SMH-Bench (2026) tests LLM smart-home agents on 1,100 human-audited tasks in HomeEnv, an executable simulator of homes from small apartments to a 31-room, 135-device house; success means the final device state meets the goal without touching unrelated devices, with GPT-5 judging clarifications and query answers. 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 over all tasks; higher is better.

Metric: Success rate (%), instance-weighted over 1,100 tasks in 7 capability categories; 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: Around February 2027. 13 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3.1 Pro (Preview)85.2#94
2Claude Sonnet 4.684.1#161
3GPT-5.479.6#123
4Qwen 3.5 397B A17B77.8#246
5Claude Haiku 4.576.2#568
6DeepSeek V3.2 (Thinking)75.5#406 (DeepSeek V3.2)
7GPT-5.4 Mini75.3#389
8GLM-570.6#260
9Qwen 3.5 Plus70#232
10Qwen 3.5 9B64.3#803
11Qwen 3.5 4B56.5#1175

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 · How It Works · Data refreshed daily, snapshot 2026-11-13.