reasoning benchmark
PaperBench is a benchmark for evaluating AI agents on their ability to replicate research papers. It tests models on complex, multi-step workflows involving code implementation, experimentation, and reproducing scientific results from academic publications.
Updated Aug 11, 2026
Higher score ranks better on this benchmark.
| 01 | AC | 93.0% | 100.0% | 3 | C | |
| 02 | MA | 63.5% | 50.0% | 3 | C | |
| 03 | MI | 52.6% | 0.0% | 3 | C |
A closer view of the leading scores on this benchmark.
The leading models and scores on this benchmark.
What PaperBench measures and how its scores work.
PaperBench is a benchmark for evaluating AI agents on their ability to replicate research papers. It tests models on complex, multi-step workflows involving code implementation, experimentation, and reproducing scientific results from academic publications.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
Common questions about PaperBench.
Qwen3.8 Max is currently ranked first with 93.0%.
PaperBench is a benchmark for evaluating AI agents on their ability to replicate research papers. It tests models on complex, multi-step workflows involving code implementation, experimentation, and reproducing scientific results from academic publications.
Yes. Higher values rank better for this benchmark.
3 model results are currently shown.
Yes. This benchmark can contribute to the current LLMBoard capability score.