GPT-5.6 Luna vs. GPT-6 Astra: Is a $1.20 Model Good Enough for Code Review? (entelligence.ai)

In a recent evaluation comparing the AI models GPT-5.6 Luna and GPT-6 Astra for code review quality, it was found that while Luna is significantly cheaper, it also displays a lower accuracy rate in identifying verified bugs. Luna costs just $0.20 per million input tokens and $1.20 per million output tokens, leading to an overall review cost of only $0.20 for 50 pull requests. In contrast, Astra's price skyrockets to $5.66 for the same workload. Luna detected 69 verified bugs compared to Astra's 92 but had a higher incidence of false positives, verifying only 74% of its findings versus Astra's 96%. This assessment is particularly important for the AI/ML community as it raises questions about the balance between cost efficiency and effectiveness in AI-driven code reviews. While Luna performs well on general correctness bugs, it struggles with security-sensitive code, highlighting a critical gap in its utility for high-stakes software development tasks. The findings suggest that combining both models might yield better results overall, capturing a wider range of bugs for a reasonable extra cost, which is vital for teams prioritizing both budget and code quality.