TriggerBench - Positive Clean PM Accuracy: leaderboard
Metric: PM accuracy (%) on the 488 positive-clean tasks, where the trigger requires the reminder; base dialogues of about 2.5K tokens; TriggerBench: 1,265 prospective-memory tasks from 488 dialogue blueprints in five dimensions (state tracking, temporal grounding, logical adherence, attention recovery, safe coding); a constraint is stated early in a dialogue and a later trigger turn calls for acting on it without being asked; GPT-4o (T=0) judges whether the reply fulfils the proactive intent; temperature 0.6; higher is better. Source: arxiv.org. Saturation forecast: Estimated already saturated. 9 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | GPT-5.2 (High) | 98.16 |
| 2 | GPT-5.2 (Medium) | 96.72 |
| 3 | Qwen 3 235B A22B 2507 FP8 (Thinking) | 92.83 |
| 4 | GPT-5.2 (Non-reasoning) | 89.75 |
| 5 | Gemma 3 27B (IT) | 76.43 |
| 6 | GPT-4.1 | 73.36 |
| 7 | Qwen 3 235B A22B 2507 Instruct | 68.65 |
| 8 | GPT-4o | 62.91 |
| 9 | Qwen 3 32B | 49.8 |
Interactive version: theaggregate.ai/benchmark?slug=triggerbench-positive-clean-pm-accuracy · How It Works · Data refreshed daily, snapshot 2026-09-29.