Agentic GraphRAG vs Long-Context Window Trade-offs
📖 Bản tiếng Việt (Vietnamese Edition) Prerequisite: Familiarity with the concepts introduced in Executive Summary. Review it first if the terminology in this part is unfamiliar. Part 1 — Agentic GraphRAG vs. Long-Context Window: Architectural Trade-offs Answer-first: Relying exclusively on 1M+ token context windows introduces quadratic latency degradation ($O(N^2)$ attention overhead), severe token cost inflation, and needle-in-a-haystack recall loss. Agentic GraphRAG extracts focused entity subgraphs to achieve 65% faster Time-To-First-Token (TTFT) at less than 10% of the inference cost. By deploying Hierarchical GraphRAG with Leiden community detection, enterprises achieve 65% faster Time-To-First-Token (TTFT) and eliminate the multi-dollar token penalties of 1M+ context window prefill while preserving cross-document multi-hop reasoning. ...