long context benchmark
CorpusQA 1M is a long-context question answering benchmark for evaluating models on approximately 1 million token contexts.
Updated Sep 5, 2026
Higher score ranks better on this benchmark.
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelDE | Score62.00% | Percentile100.00% | Participants3 | EvidenceC | Evaluated |
| Rank02 | ModelDE | Score60.50% | Percentile50.00% | Participants3 | EvidenceC | Evaluated |
| Rank03 | ModelDE | Score59.30% | Percentile0.00% | Participants3 | 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 CorpusQA 1M measures and how its scores work.
CorpusQA 1M evaluates question answering over information distributed across an extremely long input corpus.
It measures accuracy in retrieving and reasoning over information across approximately 1 million token contexts, reported as a Score 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 CorpusQA 1M.
DeepSeek-V4-Pro-Max is currently ranked first with 62.00%.
The current leaders are DeepSeek-V4-Pro-Max (62.00%), DeepSeek-V4-Flash-Max (60.50%), and DeepSeek-V4-Flash-0423 (59.30%).
DeepSeek-V4-Flash-Max has the lowest matched official input price at $0.14 input / $0.28 output per 1M tokens.
No matched runtime record is currently available.
No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.
It measures accuracy in retrieving and reasoning over information across approximately 1 million token contexts, reported as a Score ratio.
Yes. Higher values rank better for this benchmark.
3 model results are currently shown.
No. This benchmark is shown for reference but does not contribute to the overall score.
Ranking basisThis corpusqa 1m 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
DeepSeek-V4-Pro-Max currently leads CorpusQA 1M with 62.00%. 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.