long context benchmark
CorpusQA 1M is a long-context question answering benchmark designed to evaluate models at approximately 1 million token contexts. Models are scored on accuracy when retrieving and reasoning over information distributed across an extremely long input corpus.
Updated Aug 11, 2026
Higher score ranks better on this benchmark.
| 01 | DE | 62.0% | 100.0% | 2 | C | |
| 02 | DE | 60.5% | 0.0% | 2 | C |
A closer view of the leading scores on this benchmark.
The leading models and scores on this benchmark.
What CorpusQA 1M measures and how its scores work.
CorpusQA 1M is a long-context question answering benchmark designed to evaluate models at approximately 1 million token contexts. Models are scored on accuracy when retrieving and reasoning over information distributed across an extremely long input corpus.
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 CorpusQA 1M.
DeepSeek-V4-Pro-Max is currently ranked first with 62.0%.
CorpusQA 1M is a long-context question answering benchmark designed to evaluate models at approximately 1 million token contexts. Models are scored on accuracy when retrieving and reasoning over information distributed across an extremely long input corpus.
Yes. Higher values rank better for this benchmark.
2 model results are currently shown.
No. This benchmark is shown for reference but does not contribute to the overall score.