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Stop Wasting Tokens: A Smarter Alternative to JSON for LLM Pipelines

TOON (Token-Oriented Object Notation) is a compact format designed for LLM input that saves tokens by eliminating repeated structural overhead. This article explains how TOON works, when to use it, and how to get started.

SourceKDnuggetsAuthor: Kanwal Mehreen
Stop Wasting Tokens: A Smarter Alternative to JSON for LLM Pipelines
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Summary only

Under the source content permission, this page provides an editorial summary, key points, and a link to the original article.

Key points and analysis

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Key points

  • JSON wastes tokens in LLM prompts due to repeated field names; TOON reduces this by declaring fields once and listing values row by row.
  • TOON is most beneficial for inputs with repeated structured records like tickets or product catalogs; benefits diminish for nested or irregular data.
  • Best practice: keep JSON in backend, convert to TOON only for LLM input; use JSON for outputs for easy parsing.
  • Benchmark token savings, latency, and answer quality in your own pipeline to decide if TOON is right for your use case.

Highlights and analysis are generated automatically and may contain errors. Check the original source.

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