TOON (Token-Oriented Object Notation) is a compact, human-readable encoding of JSON that reduces token consumption by 30-60% for LLM applications. It uses YAML-style indentation and CSV-like tabular layouts for uniform arrays, making it ideal for AI prompts and data serialization where token efficiency matters.

How does TOON reduce tokens compared to JSON?

TOON eliminates redundant syntax like braces, brackets, and excessive quotation marks. Arrays of uniform objects are represented in tabular format with field names declared once as headers, then values listed row-by-row. This approach preserves all data while using ~40% fewer tokens than equivalent JSON.

Is TOON conversion lossless?

Yes. TOON provides deterministic, lossless round-trip conversion with JSON. You can convert JSON to TOON and back to JSON without losing any information. TOON supports the same data types as JSON: objects, arrays, strings, numbers, booleans, and null.

When should I use TOON instead of JSON?

Use TOON when working with LLMs (Large Language Models) where token consumption directly impacts costs and context window limits. TOON is especially effective for structured data with uniform arrays, API prompts, training data, and any scenario where reducing payload size while maintaining readability is important.

What does tabular array format look like?

In TOON, arrays of uniform objects use tabular format. For example, JSON like [{"id":1,"name":"Alice"},{"id":2,"name":"Bob"}] becomes: users[2]{id,name}: 1,Alice 2,Bob. Field names are declared once in the header, then each row contains comma-separated values.

Can TOON handle nested objects?

Yes. TOON uses indentation (like YAML) to represent nested structures. Nested objects increase indentation level by 2 spaces per level, making the hierarchy visually clear without braces. Complex nested structures maintain readability while staying compact.

JSON to TOON Converter

Convert between JSON and TOON format. Reduce token usage by 30-60% for LLM applications while maintaining lossless data conversion.

JSON Input

Paste your JSON here

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TOON Output

0 characters

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What is TOON Format?

TOON (Token-Oriented Object Notation) is a compact, human-readable data format specifically designed to reduce token consumption in Large Language Model (LLM) applications. Unlike JSON which uses verbose syntax with braces, brackets, and repeated keys, TOON employs YAML-style indentation and CSV-like tabular layouts for uniform arrays. This approach achieves 30-60% token reduction while maintaining complete lossless conversion with JSON—meaning you can convert JSON to TOON and back without losing any information.

The key innovation is TOON's tabular array format. Instead of repeating field names for every array element like JSON does with [{"id":1,"name":"Alice"},{"id":2,"name":"Bob"}], TOON declares field names once in a header and lists values row-by-row: users[2]{id,name}: 1,Alice 2,Bob. For nested objects, TOON uses indentation to show hierarchy without braces, similar to Python or YAML. This makes TOON especially effective for structured data, API prompts, training datasets, and any scenario where reducing payload size matters for cost or context window limits while keeping data human-readable.

TOON vs JSON Comparison

📦 JSON Format

{
  "users": [
    {
      "id": 1,
      "name": "Alice",
      "role": "admin"
    },
    {
      "id": 2,
      "name": "Bob",
      "role": "user"
    }
  ]
}

147 characters - Verbose syntax with repeated keys, braces, and brackets. Each array element fully specifies all field names.

🎒 TOON Format

users[2]{id,name,role}:
 1,Alice,admin
 2,Bob,user

54 characters (63% reduction) - Tabular format declares fields once, then lists values. Uses indentation instead of braces.

Key Features of TOON

1.30-60% Token Reduction - TOON uses ~40% fewer tokens than equivalent JSON on structured data, directly reducing LLM API costs and increasing effective context window size. Benchmarks show TOON achieves 73.9% accuracy vs JSON's 69.7% in LLM tasks while using significantly fewer tokens.
2.Lossless Round-Trip Conversion - TOON provides deterministic, lossless bidirectional conversion with JSON. Convert JSON → TOON → JSON without losing any data. Supports the same primitives (strings, numbers, booleans, null), objects, and arrays as JSON.
3.Human-Readable Structure - Unlike binary formats that sacrifice readability for size, TOON maintains clear, easy-to-read structure using indentation for nesting and tabular format for uniform arrays. Perfect for debugging, manual editing, and code review.
4.Schema-Aware Tabular Arrays - Uniform arrays automatically collapse into CSV-like tables with field headers declared once: items[3]{x,y,z}: 1,2,3 4,5,6 7,8,9. This eliminates redundant key repetition while preserving structure.
5.Strict Canonicalization - TOON enforces canonical number formatting (no exponential notation, no trailing zeros, normalized -0 to 0) ensuring consistent output and preventing subtle data differences from formatting variations.

Use Cases for TOON

🤖LLM API Prompts

Reduce token consumption in ChatGPT, Claude, or GPT-4 API calls by 30-60%. Lower costs, fit more data in context windows, and improve response quality with compact structured data.

📊Training Data Preparation

Prepare compact training datasets for fine-tuning language models. TOON's tabular format is ideal for structured examples with consistent schema across records.

⚙️Configuration Files

Use TOON for application configs where human readability matters but JSON's verbosity is wasteful. TOON's YAML-like syntax is clean and maintainable.

💾Data Serialization

Serialize API responses, database exports, or log data in compact form. TOON maintains full JSON compatibility while reducing storage and transmission costs.

Frequently Asked Questions

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