PostcondBench - Completeness: leaderboard
Metric: Comp@1 times 100 (%): expected share of methods whose generated postcondition set is test-correct and kills every mutant, one sampled postcondition set per method (k = 1, five samples drawn), averaged over the Python and Java splits (210 repository methods each) and three input settings (code only, comments only, code plus comments); higher is better. Source: arxiv.org. Saturation forecast: Around July 2027. 5 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | GPT-5 | 25.5 |
| 2 | Claude Sonnet 4.5 (Thinking) | 20.7 |
| 3 | Llama 4 Maverick | 9.4 |
| 4 | Qwen 3 32B | 5.5 |
| 5 | Gemma 3 27B | 4.4 |
Interactive version: theaggregate.ai/benchmark?slug=postcondbench-completeness · How It Works · Data refreshed daily, snapshot 2026-10-07.