Convert JSON to TOON format, Save ~40% Tokens for LLM Inputs
Instant TOON format conversion with 100% client-side processing. Reduce your AI API costs by up to 40% without compromising data integrity or structure. Perfect for developers working with large datasets, high-volume applications, and token-sensitive LLM workflows. Free forever, no signup required.
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Token Comparison
Why Choose TOON format?
TOON format (Token-Oriented Object Notation) is designed specifically for LLM efficiency. TOON format helps you save tokens and reduce AI API costs.
TOON format reduces token consumption by approximately 40% in mixed-structure benchmarks. For every 1,000 API calls with 10KB datasets, save $15-30 in API costs depending on your LLM provider. Perfect for large datasets sent to LLMs, it significantly cuts expenses while maintaining complete data integrity and structure.
TOON format provides a clean, tabular structure with explicit length declarations and field headers that LLMs can easily parse and understand. Using length-prefixed encoding and columnar storage, it eliminates nested brackets and redundant punctuation that slow down token processing, resulting in faster inference times.
TOON format supports deterministic round-trip conversion to and from JSON with zero data loss. Convert JSON→TOON→JSON preserving all values, types, and structure. The conversion is reversible and deterministic, making it perfect for workflows where you need both formats or want to maintain compatibility with existing JSON tools.
All processing happens directly in your browser using JavaScript—your data never leaves your device or gets sent to any server. TOON format conversion is completely private, GDPR-compliant, and secure. No account signup, no data collection, no cloud processing. Get instant results with complete peace of mind.
When to Use TOON format
Understand the sweet spot for maximum token savings
- Arrays of uniform objects like product catalogs, user lists, or log entries - works exceptionally well with 100+ items
- Tabular data with repeated structure - e.g., CSV-like data, database query results, analytics reports
- LLM prompt inputs with large datasets (10KB+) - where you'll see the most significant token and cost reductions
- Reducing API costs for high-volume applications - saves money on every single request
- Batch processing of structured data - ETL pipelines, data migrations, bulk imports/exports
- Deeply nested single objects with complex hierarchies - standard JSON is more efficient for these
- Highly variable object structures where each item has different fields - overhead outweighs benefits
- Very small datasets (<100 tokens / <10 items) - conversion overhead makes it counterproductive
- Data that needs standard JSON tooling like jq, JSON Schema validation, or existing parsers
- Human-readable configuration files like package.json or app configs - readability matters more than tokens
Frequently Asked Questions
Common questions about TOON format
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