AutoBuddy-Bench - Discovery Precision: leaderboard
AutoBuddy-Bench v1, same 120-task simulated workplace, three runs per backbone, native Discovery Precision on 0–1 scale. Tasks discovered from workplace history, then executed through supplied tools. Execution is conditional on correctly discovered ground-truth tasks; precision/recall/F1 and end-to-end use their separately defined denominators. Source standard deviation retained in primary table, not treated as independent sampling SE. Exact source backbone and AutoBuddy harness remain a run identity; no model release is inferred.
Metric: Discovery Precision (0–1). Source: arxiv.org. Saturation forecast: Rough model projection: around 2026. 17 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | gpt-5.6-sol (AutoBuddy Run: protocol=120-task-world; runs=3; harness=AutoBuddy) | 0.95 | |
| 2 | gpt-5.5 (AutoBuddy Run: protocol=120-task-world; runs=3; harness=AutoBuddy) | 0.94 | |
| 3 | claude-opus-5.5 (AutoBuddy Run: protocol=120-task-world; runs=3; harness=AutoBuddy) | 0.91 | |
| 4 | gpt-6.1-sol (AutoBuddy Run: protocol=120-task-world; runs=3; harness=AutoBuddy) | 0.9 | |
| 5 | gpt-6-luna (AutoBuddy Run: protocol=120-task-world; runs=3; harness=AutoBuddy) | 0.9 | |
| 6 | gpt-5.4 (AutoBuddy Run: protocol=120-task-world; runs=3; harness=AutoBuddy) | 0.87 | |
| 7 | Kimi-K2.6 (AutoBuddy Run: protocol=120-task-world; runs=3; harness=AutoBuddy) | 0.86 | |
| 8 | DeepSeek-V4.1-Flash (AutoBuddy Run: protocol=120-task-world; runs=3; harness=AutoBuddy) | 0.85 | |
| 9 | claude-opus-4.8 (AutoBuddy Run: protocol=120-task-world; runs=3; harness=AutoBuddy) | 0.85 | |
| 10 | claude-sonnet-5 (AutoBuddy Run: protocol=120-task-world; runs=3; harness=AutoBuddy) | 0.83 |
Interactive version: theaggregate.ai/benchmark?slug=autobuddy-bench-discovery-precision · How It Works · Data refreshed daily, snapshot 2026-11-12.