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LLM Stats
RULER
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.
Evaluation context and evidence
- Source
- LLM Stats
- Publisher
- Not recorded
- Benchmark release
- Not recorded
- Collected
- 2026-08-17
- Modality
- text
These are source-reported observations, not independent reruns by this site. Check the task version, evaluation protocol, unit and reporting date before comparing models. Results from different setups are not a universal ranking.
Original sources
Reported results 4
Shown in source observation order, not ranked. Dates retain the precision provided by the source.
| Model | Value | Unit | Protocol | Reported date and basis | Source |
|---|---|---|---|---|---|
| Nemotron 3 Ultra (550B A55B) | 0.947 | Not recorded | Not recorded | 2026-06-04 · model_announcement | LLM Stats |
| Nemotron 3 Super (120B A12B) | 0.9175 | Not recorded | Not recorded | 2026-03-11 · model_announcement | LLM Stats |
| Phi-3.5-MoE-instruct | 0.871 | Not recorded | Not recorded | 2024-08-23 · model_announcement | LLM Stats |
| Phi-3.5-mini-instruct | 0.841 | Not recorded | Not recorded | 2024-08-23 · model_announcement | LLM Stats |