reasoning benchmark
RULER v1 is a synthetic long-context benchmark for measuring how model quality degrades as input length increases. This packaging follows the public standalone NVIDIA RULER implementation with 13 official tasks spanning retrieval, multi-hop tracing, aggregation, and QA.
Updated Aug 7, 2026
Sorted by the source-provided rank. Higher score is better according to the registry.
| 1 | NV | 94.7% | 100.0% | 4 | C | |
| 2 | NV | 91.8% | 66.7% | 4 | C | |
| 3 | MI | 87.1% | 33.3% | 4 | C | |
| 4 | MI | 84.1% | 0.0% | 4 | C |
Top published rows on the benchmark's original scale.
The top published results on this benchmark's own scale.
Definition and scoring fields from the benchmark registry.
RULER v1 is a synthetic long-context benchmark for measuring how model quality degrades as input length increases. This packaging follows the public standalone NVIDIA RULER implementation with 13 official tasks spanning retrieval, multi-hop tracing, aggregation, and QA.
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 RULER.
Nemotron 3 Ultra (550B A55B) is currently ranked first with 94.7%.
RULER v1 is a synthetic long-context benchmark for measuring how model quality degrades as input length increases. This packaging follows the public standalone NVIDIA RULER implementation with 13 official tasks spanning retrieval, multi-hop tracing, aggregation, and QA.
Yes. Higher values rank better for this benchmark.
4 unique published model results are currently shown.
This benchmark is preserved as source-native evidence but is not eligible for the current overall score.