Small PRs + Performance Optimization (Precision)
↗
Best for Medium Ruby PRs ↗
Best for Bug Fixes ↗
Typescript + Correctness ↗
Ruby + Medium PRs (Recall) ↗
Best for Ui ↗
Bug Fixes + Cross-File ↗
Best for Reliability ↗
Best for Concurrency ↗
Ruby + Correctness ↗
Ruby + Correctness ↗
Best for Caching ↗
Best for Go ↗
Best for Small PRs ↗
Best for Scheduling ↗
Best for File Context ↗
Best for Security ↗
Security Critical ↗
Best for High Risk ↗
Best for Python ↗
Best for Medium Python PRs ↗
Best for Moderate Bugs ↗
Highest Recall ↗
Best for Authentication ↗
High Risk Auth ↗
Best for Critical Risk ↗
Best for Medium Java PRs ↗
Best for Features ↗
Best for Moderate Code ↗
Best for Complex Code ↗
Complex & Subtle ↗
Best for Correctness ↗
Best for Java ↗
Best for Large PRs ↗
Highest F1 ↗
Best for Typescript ↗
Best for Subtle Bugs ↗
Best for Cross-File ↗
Best for Medium PRs ↗
Best for Medium Risk ↗
Best for Reliability ↗
Best for Concurrency ↗
Best for Ruby ↗
Tool performance varies by context. Filter and tailor the benchmark to
fit your use case:
Judge Model
Language
PR Size
Domain
+ More...
Code Complexity
Review Difficulty
Risk Level
Context Required
Primary Concern
Show Metrics
CURRENT RESULTS
All Languages
Performance Metrics
#
Tool
Precision (%)
Recall (%)
F1 Score (%)
True Positives
PRs Evaluated
F1 Score by Tool
Repositories Used
The offline benchmark draws from a
diverse set of open-source repositories spanning different
languages,
frameworks, and domains — from infrastructure and observability
tools to web platforms and security projects.
This variety ensures our results reflect
how AI reviewers perform across real-world codebases,
not just one type of software.
