OpenRCA
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.
Claude Opus 4.6 from Anthropic currently leads the OpenRCA leaderboard with a score of 0.349 across 1 evaluated AI models.
What OpenRCA measures
OpenRCA is a text benchmark that evaluates large language models on reasoning, agents, and code tasks. LLM Stats tracks 1 model on this benchmark, with a maximum possible score of 1. Current average across reported models is 0.3, with the leader reaching 0.3.
Compare leaders on the best AI for reasoning, best AI for agents and best AI for code leaderboards.
Claude Opus 4.6 leads with 34.9%.
Progress Over Time
Interactive timeline showing model performance evolution on OpenRCA
OpenRCA Leaderboard
| Context | Cost | License | ||||
|---|---|---|---|---|---|---|
| 1 | Anthropic | — | 1.0M | $5.00 / $25.00 |
FAQ
Common questions about OpenRCA.
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