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RepoQA benchmark
AI model leaderboard for the RepoQA benchmark. Compare how large language models score on RepoQA, see the full ranking, and understand what this AI benchmark measures. Kimi Linear currently leads with 68.5. Repository-level long-context code understanding — find a specified function within a large code repo dump.
Leaderboard
| # | Model | Organization | Score | Variant | Source |
|---|---|---|---|---|---|
| #1 | Kimi Linear | Moonshot | 68.5 | long-context-128k | official ↗ |
Frequently asked questions about RepoQA
What is the RepoQA benchmark?
Repository-level long-context code understanding — find a specified function within a large code repo dump.
How is the RepoQA benchmark scored?
RepoQA is scored using the accuracy metric, where a higher score is better. GenAIList aggregates reported scores from model providers and papers into a single ranked leaderboard.
Which AI model scores highest on RepoQA?
As of the latest reported scores on GenAIList, Kimi Linear achieves the highest result on RepoQA with a score of 68.5.
Is a higher RepoQA score better?
Yes. On RepoQA a higher score indicates better performance, so models near the top of the leaderboard are the strongest.