Reduce LLM Token Waste in RAG with Markdown

Short summary

Feeding raw HTML to LLMs wastes tokens on markup, scripts, and styling that don't represent actual content. Converting the final DOM to Markdown via headless browser rendering reduces token consumption by up to 94% while preserving semantic structure. This improves both cost efficiency and retrieval accuracy in RAG pipelines by feeding the model dense, high-signal information.

• •Raw HTML causes 50,000+ token bloat from markup; Markdown achieves 3,000-token equivalent with 94% reduction
• •HTML noise degrades embedding quality and retrieval relevance; Markdown preserves semantic structure natively
• •Headless browser execution with DOM sanitization handles modern SPAs and removes boilerplate (nav, footer, ads)

Generated with AI, which can make mistakes.