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tech 15 September 2026

GPT-5.6 Luna vs GPT-6 Astra: Is a $1.20 Model Good Enough for Code Review?

Explore how GPT-5.6 Luna and GPT-6 Astra stack up for code review. Is Luna efficient enough at a lower cost, or is Astra worth the extra investment?

Article inspired by the original source
GPT-5.6 Luna vs. GPT-6 Astra: Is a $1.20 Model Good Enough for Code Review? ↗ entelligence.ai

Introduction

In a world where code review is crucial for software quality, choosing the right AI model can make all the difference. Today, we examine two popular models: GPT-5.6 Luna and GPT-6 Astra. With Luna costing $1.20 per million output tokens compared to Astra's $50, the question is simple: Is Luna sufficient for daily code review?

Cost and Efficiency

GPT-5.6 Luna costs $0.20 per million input tokens and $1.20 per million output tokens. In comparison, GPT-6 Astra is priced at $10 and $50 respectively. For the same pull requests, a review by Luna costs $0.0041, while Astra costs $0.113, a 28x difference.

Test Results

In a series of 50 pull requests from projects like Cal.com and Grafana, Luna detected 69 verified bugs compared to 92 for Astra. However, Luna failed to verify 24 of its 93 findings, while Astra missed only 4 out of 96. In terms of security, Luna identified 9 bugs compared to 19 for Astra.

When to Use Luna?

Luna excels in detecting everyday correctness bugs but is not recommended for critical authentication or permission code. For projects needing comprehensive security analysis, Astra remains the preferred choice.

Conclusion

Luna offers an economical solution for common bugs, but Astra justifies its cost for high-security needs. It largely depends on the project's nature and specific requirements.

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GPT-5.6 Luna GPT-6 Astra code review AI models cost efficiency
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