reasoning benchmark
FrontierScience Research Leaderboard
FrontierScience Research is a benchmark evaluating AI models on cutting-edge scientific research questions requiring deep domain expertise, multi-step reasoning, and synthesis of complex scientific concepts across disciplines.
Updated Aug 17, 2026
Models4
Model coverage4
MetricScore
EvidenceB
FrontierScience Research Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelME | Score38.3% | Percentile100.0% | Participants4 | EvidenceC | Evaluated |
| Rank02 | ModelBY | Score33.3% | Percentile66.7% | Participants4 | EvidenceC | Evaluated |
| Rank03 | ModelBY | Score28.3% | Percentile33.3% | Participants4 | EvidenceC | Evaluated |
| Rank04 | ModelTE | Score21.3% | Percentile0.0% | Participants4 | EvidenceC | Evaluated |
FrontierScience Research Highlights
The leading models and scores on this benchmark.
FrontierScience Research Score Distribution
A closer view of the leading scores on this benchmark.
The Top AI Models for FrontierScience Research
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis frontierscience research 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.
- 01MEMuse SparkMeta
- Score
- 38.3%
Strengths
- Ranks #1 of 4 compared models
- 100th percentile on this benchmark
- C evidence result
Considerations
- This result measures FrontierScience Research, not total model capability
- 02BYSeed 2.1 TurboByteDance
- Score
- 33.3%
Strengths
- Ranks #2 of 4 compared models
- 67th percentile on this benchmark
- C evidence result
Considerations
- This result measures FrontierScience Research, not total model capability
- 03BYSeed 2.1 ProByteDance
- Score
- 28.3%
Strengths
- Ranks #3 of 4 compared models
- 33th percentile on this benchmark
- C evidence result
Considerations
- This result measures FrontierScience Research, not total model capability
- 04TEHy3Tencent
- Score
- 21.3%
Strengths
- Ranks #4 of 4 compared models
- 0th percentile on this benchmark
- C evidence result
Considerations
- This result measures FrontierScience Research, not total model capability
Selection summary
Best AI Models for FrontierScience Research
Muse Spark currently leads FrontierScience Research with 38.3%. 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 FrontierScience Research?
What FrontierScience Research measures and how its scores work.
FrontierScience Research is a benchmark evaluating AI models on cutting-edge scientific research questions requiring deep domain expertise, multi-step reasoning, and synthesis of complex scientific concepts across disciplines.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- FrontierScience Research
- Modality
- text
- Primary category
- reasoning
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- frontierscience-research|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about FrontierScience Research.
Which model scores highest on FrontierScience Research?
Muse Spark is currently ranked first with 38.3%.
What does FrontierScience Research measure?
FrontierScience Research is a benchmark evaluating AI models on cutting-edge scientific research questions requiring deep domain expertise, multi-step reasoning, and synthesis of complex scientific concepts across disciplines.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
4 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.