Stop Trusting Vibes: A Reproducible Harness for Comparing AI Coding Models on Your Own Codebase

Many AI coding model comparisons rely on subjective vibes rather than objective data. To solve this, a reproducible harness allows developers to test models against their own repositories, legacy modules, and specific build systems. This tool measures time to first token, total task latency, and mechanical success, such as compilation. By using fixed tasks and deterministic scoring rubrics, developers can replace anecdotal evidence with actual numbers to decide between local setups and free hosted models.