This paper consolidates the Evans’ Law research program through November 2025, introducing new multimodal empirical results, cross-model comparisons (GPT-4, GPT-5, Gemini 2.5 Flash, Claude 3.5, Grok-1, Mistral Large, Mixtral 8×7B, Nova 1, Qwen 2.5 72B), and governance recommendations. The updated regression, L = 1773 × M^0.79 (R² ≈ 0.97), defines the observed coherence scaling across large language models, with multimodal and hybrid systems analyzed separately. The study presents the Aggregate Coherence Index (ACI) and extends Evans’ Law to account for modality and complexity effects. Findings demonstrate that coherence degradation follows a predictable power-law pattern, requiring new transparency norms in model evaluation and platform governance.