reasoning benchmark
OpenRCA Leaderboard
OpenRCA is a benchmark for evaluating AI models on root cause analysis tasks. For each failure case, the model receives 1 point if all generated root-cause elements match the ground-truth ones, and 0 points if any mismatch is identified. The overall accuracy is the average score across all failure cases.
Updated Aug 17, 2026
Models1
Model coverage1
MetricScore
EvidenceB
OpenRCA Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelAN | Score34.9% | Percentile100.0% | Participants1 | EvidenceC | Evaluated |
OpenRCA Highlights
The leading models and scores on this benchmark.
The Top AI Models for OpenRCA
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis openrca AI model leaderboard uses descending score in the benchmark's original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
- 01ANClaude Opus 4.6Anthropic
- Score
- 34.9%
- Price
- $5.0 input / $25 output per 1M tokens
- Speed
- Up to 17 tok/s via Anthropic
Strengths
- Ranks #1 of 1 compared models
- 100th percentile on this benchmark
- C evidence result
Considerations
- This result measures OpenRCA, not total model capability
Selection summary
Best AI Models for OpenRCA
Claude Opus 4.6 currently leads OpenRCA with 34.9%. 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.
What is OpenRCA?
What OpenRCA measures and how its scores work.
OpenRCA is a benchmark for evaluating AI models on root cause analysis tasks. For each failure case, the model receives 1 point if all generated root-cause elements match the ground-truth ones, and 0 points if any mismatch is identified. The overall accuracy is the average score across all failure cases.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- OpenRCA
- Modality
- text
- Primary category
- reasoning
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- openrca|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about OpenRCA.
Which model scores highest on OpenRCA?
Claude Opus 4.6 is currently ranked first with 34.9%.
What does OpenRCA measure?
OpenRCA is a benchmark for evaluating AI models on root cause analysis tasks. For each failure case, the model receives 1 point if all generated root-cause elements match the ground-truth ones, and 0 points if any mismatch is identified. The overall accuracy is the average score across all failure cases.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
1 model results are currently shown.
Does this benchmark affect the overall score?
No. This benchmark is shown for reference but does not contribute to the overall score.