FGRF v3.0 is a scale-dependent structural probe for analyzing LLM weight matrices, validating topological complexity metrics across trained and untrained models. Testing on Qwen2.5, SmolLM2, and GPT-2 shows trained models have lower topological complexity and higher Hausdorff dimension in key-value projections, with reproducible signatures across five seeds and three architectures.