Determine whether frontier-scale LLMs retain the CodeHealth–inference-cost association

Determine whether the largest and most capable large language models, including models such as Opus 5.5 or GPT-6, exhibit the same negative association between CodeHealth and token cost for agentic code review and repair.

Background

The study observed a negative CodeHealth coefficient for each of the three evaluated current-generation LLMs, including Claude Sonnet 5, but none of the tested systems represented its provider’s flagship tier. The authors therefore leave unresolved whether the observed relationship is a property of LLM-based code review more generally or only of the particular models evaluated.

Addressing this problem would require evaluating substantially larger and more capable LLMs under a design that can distinguish model capability from provider, architecture, serving, caching, and other implementation differences.