factuality benchmark
LongFact evaluates factual precision over long-form generations containing many individual claims. Each claim is extracted and verified, and the model is scored on claim-level precision, measuring whether extended responses introduce unsupported or false statements.
Updated Aug 7, 2026
Sorted by the source-provided rank. Higher score is better according to the registry.
| 1 | MI | 98.0% | 100.0% | 1 | C |
The top published results on this benchmark's own scale.
Definition and scoring fields from the benchmark registry.
LongFact evaluates factual precision over long-form generations containing many individual claims. Each claim is extracted and verified, and the model is scored on claim-level precision, measuring whether extended responses introduce unsupported or false statements.
Scores are shown in ratio. The current registry marks this benchmark as not independently verified with evidence level B.
Source-native results are preserved. Eligibility for the overall LLMBoard score is a separate policy decision.
Common questions about LongFact.
MAI-Thinking-1 is currently ranked first with 98.0%.
LongFact evaluates factual precision over long-form generations containing many individual claims. Each claim is extracted and verified, and the model is scored on claim-level precision, measuring whether extended responses introduce unsupported or false statements.
Yes. Higher values rank better for this benchmark.
1 unique published model results are currently shown.
This benchmark is preserved as source-native evidence but is not eligible for the current overall score.