AdaPlanBench - Effectiveness: leaderboard

AdaPlanBench (2026) gives LLM agents 307 household planning tasks whose world and user constraints stay hidden until a proposed plan violates one, so the agent must re-plan from feedback; boards use the mid-level constraint profile. This board is the mean 1 to 5 rubric score of three LLM judges for whether the plans, carried out as written, would achieve the goal; higher is better.

Metric: Effectiveness rubric (1-5): whether the plan, carried out as written, would achieve the goal; mean score (1-5) from three rubric judges (GPT-4.1, DeepSeek-V3.2, Qwen3.6-Flash) over the agent's plans, 307 household planning tasks with progressively revealed world and user constraints at the mid-level constraint profile: a hidden constraint is disclosed only when a proposed plan violates it (GPT-5.4 constraint judges), and the agent re-plans within the turn budget; temperature 0 (GPT-5 family at its fixed default, mean of three runs); higher is better. Source: arxiv.org. Saturation forecast: Estimated already saturated. 10 models tracked.

Top models

#ModelScoreOverall rank
1GPT-54.57#167
2GPT-5 Mini4.37#348
3Gemini 3.1 Pro (Preview)4.06#94
4Gemini 3 Flash4#164
5GPT-5 Nano3.97#889
6DeepSeek V4 Flash3.87#258
7Llama 3.3 70B Instruct3.24#1357
8Qwen 3 32B3.09#960
9Qwen 3 14B3.03#1233
10Qwen 3 8B2.96#1830

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

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