long context benchmark
SQuALITY (Summarization-format QUestion Answering with Long Input Texts, Yes!) is a long-document summarization dataset built by hiring highly-qualified contractors to read public-domain short stories (3000-6000 words) and write original summaries from scratch. Each document has five summaries: one overview and four question-focused summaries. Designed to address limitations in existing summarization datasets by providing high-quality, faithful summaries.
Updated Aug 17, 2026
Higher score ranks better on this benchmark.
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelMI | Score24.3% | Percentile100.0% | Participants5 | EvidenceC | Evaluated |
| Rank02 | ModelMI | Score24.1% | Percentile75.0% | Participants5 | EvidenceC | Evaluated |
| Rank03 | ModelAM | Score19.8% | Percentile50.0% | Participants5 | EvidenceC | Evaluated |
| Rank04 | ModelAM | Score19.2% | Percentile25.0% | Participants5 | EvidenceC | Evaluated |
| Rank05 | ModelAM | Score18.8% | Percentile0.0% | Participants5 | EvidenceC | Evaluated |
The leading models and scores on this benchmark.
A closer view of the leading scores on this benchmark.
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis squality 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.
Selection summary
Phi-3.5-mini-instruct currently leads SQuALITY with 24.3%. 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 SQuALITY measures and how its scores work.
SQuALITY (Summarization-format QUestion Answering with Long Input Texts, Yes!) is a long-document summarization dataset built by hiring highly-qualified contractors to read public-domain short stories (3000-6000 words) and write original summaries from scratch. Each document has five summaries: one overview and four question-focused summaries. Designed to address limitations in existing summarization datasets by providing high-quality, faithful summaries.
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 SQuALITY.
Phi-3.5-mini-instruct is currently ranked first with 24.3%.
SQuALITY (Summarization-format QUestion Answering with Long Input Texts, Yes!) is a long-document summarization dataset built by hiring highly-qualified contractors to read public-domain short stories (3000-6000 words) and write original summaries from scratch. Each document has five summaries: one overview and four question-focused summaries. Designed to address limitations in existing summarization datasets by providing high-quality, faithful summaries.
Yes. Higher values rank better for this benchmark.
5 model results are currently shown.
Yes. This benchmark can contribute to the current LLMBoard capability score.