language benchmark
SQuALITY is a long-document summarization dataset based on public-domain short stories of 3000-6000 words, with one overview summary and four question-focused summaries per document.
Updated Sep 5, 2026
Higher score ranks better on this benchmark.
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelMI | Score24.30% | Percentile100.00% | Participants5 | EvidenceC | Evaluated |
| Rank02 | ModelMI | Score24.10% | Percentile75.00% | Participants5 | EvidenceC | Evaluated |
| Rank03 | ModelAM | Score19.80% | Percentile50.00% | Participants5 | EvidenceC | Evaluated |
| Rank04 | ModelAM | Score19.20% | Percentile25.00% | Participants5 | EvidenceC | Evaluated |
| Rank05 | ModelAM | Score18.80% | Percentile0.00% | 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.
What SQuALITY measures and how its scores work.
SQuALITY (Summarization-format QUestion Answering with Long Input Texts, Yes!) is a language benchmark dataset for long-document summarization.
SQuALITY measures summarization performance using the metric Score, reported as a ratio.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
LLM Stats. 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 24.30%.
The current leaders are Phi-3.5-mini-instruct (24.30%), Phi-3.5-MoE-instruct (24.10%), and Nova Pro (19.80%).
Nova Micro has the lowest matched official input price at $0.04 input / $0.14 output per 1M tokens.
The fastest matched records are Phi-3.5-mini-instruct (23.00 tok/s via Azure).
No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.
SQuALITY measures summarization performance using the metric Score, reported as a ratio.
Yes. Higher values rank better for this benchmark.
5 model results are currently shown.
No. This benchmark is shown for reference but does not contribute to the overall score.
Ranking basisThis squality AI model leaderboard uses descending score in the benchmark 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 24.30%. 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.