Definition
Token Optimization is the strategic management of LLM input and output payloads to minimize costs and latency by removing redundant data, summarizing context, or prioritizing high-relevance chunks. The primary trade-off involves balancing aggressive context pruning for speed and cost against the risk of losing granular details required for complex reasoning or accurate RAG grounding.
Focuses on linguistic unit management for LLM throughput, not hardware memory or database storage efficiency.
"The Editor's Red Pen: Striking out redundant words in a manuscript to meet a strict page count while ensuring the plot remains coherent."
- Context Window(Constraint)
- Prompt Compression(Methodology)
- Lost in the Middle(Optimization Driver)
- Top-K Retrieval(Prerequisite)
Conceptual Overview
Token Optimization is the strategic management of LLM input and output payloads to minimize costs and latency by removing redundant data, summarizing context, or prioritizing high-relevance chunks. The primary trade-off involves balancing aggressive context pruning for speed and cost against the risk of losing granular details required for complex reasoning or accurate RAG grounding.
Disambiguation
Focuses on linguistic unit management for LLM throughput, not hardware memory or database storage efficiency.
Visual Analog
The Editor's Red Pen: Striking out redundant words in a manuscript to meet a strict page count while ensuring the plot remains coherent.