reasoning benchmark
SuperGLUE Leaderboard
SuperGLUE is a new benchmark styled after GLUE with a new set of more difficult language understanding tasks, improved resources, and a new public leaderboard. It includes 8 primary tasks: BoolQ (Boolean Questions), CB (CommitmentBank), COPA (Choice of Plausible Alternatives), MultiRC (Multi-Sentence Reading Comprehension), ReCoRD (Reading Comprehension with Commonsense Reasoning), RTE (Recognizing Textual Entailment), WiC (Word-in-Context), and WSC (Winograd Schema Challenge). The benchmark evaluates diverse language understanding capabilities including reading comprehension, commonsense reasoning, causal reasoning, coreference resolution, textual entailment, and word sense disambiguation across multiple domains.
Updated Aug 17, 2026
Models1
Model coverage1
MetricScore
EvidenceB
SuperGLUE Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelOP | Score75.0% | Percentile100.0% | Participants1 | EvidenceC | Evaluated |
SuperGLUE Highlights
The leading models and scores on this benchmark.
The Top AI Models for SuperGLUE
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis superglue 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.
- 01OPo1-miniOpenAI
- Score
- 75.0%
- Speed
- Up to 115 tok/s via OpenAI
Strengths
- Ranks #1 of 1 compared models
- 100th percentile on this benchmark
- C evidence result
Considerations
- This result measures SuperGLUE, not total model capability
Selection summary
Best AI Models for SuperGLUE
o1-mini currently leads SuperGLUE with 75.0%. 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 SuperGLUE?
What SuperGLUE measures and how its scores work.
SuperGLUE is a new benchmark styled after GLUE with a new set of more difficult language understanding tasks, improved resources, and a new public leaderboard. It includes 8 primary tasks: BoolQ (Boolean Questions), CB (CommitmentBank), COPA (Choice of Plausible Alternatives), MultiRC (Multi-Sentence Reading Comprehension), ReCoRD (Reading Comprehension with Commonsense Reasoning), RTE (Recognizing Textual Entailment), WiC (Word-in-Context), and WSC (Winograd Schema Challenge). The benchmark evaluates diverse language understanding capabilities including reading comprehension, commonsense reasoning, causal reasoning, coreference resolution, textual entailment, and word sense disambiguation across multiple domains.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- SuperGLUE
- Modality
- text
- Primary category
- reasoning
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- superglue|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about SuperGLUE.
Which model scores highest on SuperGLUE?
o1-mini is currently ranked first with 75.0%.
What does SuperGLUE measure?
SuperGLUE is a new benchmark styled after GLUE with a new set of more difficult language understanding tasks, improved resources, and a new public leaderboard. It includes 8 primary tasks: BoolQ (Boolean Questions), CB (CommitmentBank), COPA (Choice of Plausible Alternatives), MultiRC (Multi-Sentence Reading Comprehension), ReCoRD (Reading Comprehension with Commonsense Reasoning), RTE (Recognizing Textual Entailment), WiC (Word-in-Context), and WSC (Winograd Schema Challenge). The benchmark evaluates diverse language understanding capabilities including reading comprehension, commonsense reasoning, causal reasoning, coreference resolution, textual entailment, and word sense disambiguation across multiple domains.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
1 model results are currently shown.
Does this benchmark affect the overall score?
No. This benchmark is shown for reference but does not contribute to the overall score.