TOON vs TRON vs JSON, YAML, and CSV for LLM Applications

▤ Summary

This article evaluates TOON as a token-efficient alternative to JSON, YAML, CSV, and TRON for LLM workflows. It focuses on how different data formats affect API token usage in tasks like RAG, function calling, few-shot prompting, and structured response handling. The examples show that TOON can substantially reduce token counts compared with JSON and YAML in many LLM-oriented payloads. The piece also highlights tradeoffs around readability, expressiveness, and suitability for different application patterns.

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