reasoning benchmark
PaperBench Leaderboard
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 17, 2026
Models3
Model coverage3
MetricScore
EvidenceB
PaperBench Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelAC | Score93.0% | Percentile100.0% | Participants3 | EvidenceC | Evaluated |
| Rank02 | ModelMA | Score63.5% | Percentile50.0% | Participants3 | EvidenceC | Evaluated |
| Rank03 | ModelMI | Score52.6% | Percentile0.0% | Participants3 | EvidenceC | Evaluated |
PaperBench Highlights
The leading models and scores on this benchmark.
PaperBench Score Distribution
A closer view of the leading scores on this benchmark.
The Top AI Models for PaperBench
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis paperbench AI model leaderboard uses descending score in the benchmark's original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
- 01ACQwen3.8 MaxAlibaba Cloud / Qwen Team
- Score
- 93.0%
- Price
- $2.0 input / $6.0 output per 1M tokens
Strengths
- Ranks #1 of 3 compared models
- 100th percentile on this benchmark
- C evidence result
Considerations
- This result measures PaperBench, not total model capability
- 02MAKimi K2.5Moonshot AI
- Score
- 63.5%
- Price
- $0.60 input / $3.0 output per 1M tokens
Strengths
- Ranks #2 of 3 compared models
- 50th percentile on this benchmark
- C evidence result
Considerations
- This result measures PaperBench, not total model capability
- 03MIMiniMax M3MiniMax
- Score
- 52.6%
- Price
- $0.30 input / $1.2 output per 1M tokens
- Speed
- Up to 214 tok/s via Together
Strengths
- Ranks #3 of 3 compared models
- 0th percentile on this benchmark
- C evidence result
Considerations
- This result measures PaperBench, not total model capability
Selection summary
Best AI Models for PaperBench
Qwen3.8 Max currently leads PaperBench with 93.0%. It is the top model on this specific benchmark, while the best LLM for the broader task should also be checked against other benchmarks, price and runtime.
Use this leaderboard with the supporting benchmark results and coverage details above. A leaderboard position summarizes the selected ranking signal; it does not replace workload-specific testing.
What is PaperBench?
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.
- Family
- PaperBench
- Modality
- text
- Primary category
- reasoning
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- paperbench|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about PaperBench.
Which model scores highest on PaperBench?
Qwen3.8 Max is currently ranked first with 93.0%.
What does PaperBench measure?
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.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
3 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.