Holistic cross-comparison evaluates paired ungrounded and grounded sessions to map the divide between an LLM's static parametric memory and real-time search reality. By cross-referencing rank discrepancies across multiple runs, the system isolates emergent search-only discoveries from legacy training hallucinations, while pinpointing converged attributes where live retrieval and underlying model weights fully agree.