🚀 TOON vs JSON: The Future of Data Formatting for LLMs 🚀

🚀 TOON vs JSON: The Future of Data Formatting for LLMs 🚀

If you’re building AI applications, your API bills are probably climbing each month. Did you know you could be paying 30–60% more if you’re using JSON to structure your data?

Meet TOON – Token-Oriented Object Notation A new data format purpose-built for the AI era, TOON delivers:

30–60% fewer tokens vs. JSON

Lower API costs: Save $300–$600/month for every $1,000 spent on OpenAI/Anthropic APIs

Improved model accuracy: Cleaner structure actually helps LLMs parse data better

Seamless support across top providers (OpenAI, Anthropic, Google, etc.)

When is TOON the right choice?

• Uniform tabular data for LLM prompts
• RAG pipelines, agent frameworks, high-volume API calls
• Internal AI workflows where every token matters

Best practice:

• Use JSON for external APIs and third-party integrations
• Convert to TOON when feeding data to LLMs for serious token savings
• We’re seeing a fundamental shift—optimizing formats for LLMs, not just humans.

Have you experimented with TOON in your AI workflows? What savings have you achieved? Let’s discuss in the comments!

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Originally posted on LinkedIn · 225 likes · 27 comments