TOON vs JSON vs YAML: Which Data Format Should You Use?

When building applications that interact with Large Language Models (LLMs), choosing the right data format can make or break your efficiency. Should you stick with JSON, the familiar standard? Switch to YAML for readability? Or adopt TOON, the emerging format designed specifically for AI?

This comprehensive guide compares TOON, JSON, and YAML across critical dimensions—token efficiency, readability, performance, compatibility, and real-world use cases. By the end, you'll know exactly which format to use for every scenario, including how to convert JSON to TOON and optimize your LLM API costs.

What Are TOON, JSON, and YAML?

JSON (JavaScript Object Notation)

JSON uses curly braces and commas to structure data. It's been the universal standard for APIs, web services, and general data interchange since 2002.

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

Tokens Used: ~89 tokens for the above example

YAML (YAML Ain't Markup Language)

YAML prioritizes human readability by using indentation instead of braces. It's popular for configuration files (Kubernetes, Docker, CI/CD pipelines).

users:
  - id: 1
    name: Alice
    role: admin
  - id: 2
    name: Bob
    role: user

Tokens Used: ~110 tokens (more than JSON due to verbose key repetition)

TOON (Token-Oriented Object Notation)

TOON combines YAML's indentation with CSV's tabular structure and optimizes both for LLM token efficiency. It's purpose-built for AI systems.

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

Tokens Used: ~45 tokens (50% fewer than JSON, 60% fewer than YAML)

Side-by-Side Comparison: TOON vs JSON vs YAML

Winner: TOON for LLM use cases, YAML for human configuration, JSON for familiarity.

Token Efficiency: Real Benchmarks

Dataset: 100 GitHub repositories with 11 fields each

How TOON Reduces Tokens

Savings Mechanism: TOON declares object keys once in a header instead of repeating them for every row. On large uniform datasets, this compounds dramatically.

Token Savings by Dataset Type

When to Use TOON vs JSON vs YAML

Real-World Scenarios: Cost Savings Analysis

Scenario 1: ChatGPT API with 100 User Records

Scenario 2: Analytics Dashboard - 180 Days of Daily Metrics

Scenario 3: RAG System - Embedding 10,000 Documents

How to Convert JSON to TOON

Method 1: Online Converter (Easiest)

Visit our free JSON to TOON converter and paste your JSON:

{
  "users": [
    { "id": 1, "name": "Alice", "role": "admin" },
    { "id": 2, "name": "Bob", "role": "user" },
    { "id": 3, "name": "Charlie", "role": "user" }
  ]
}

Instant Output:

users[3]{id,name,role}:
  1,Alice,admin
  2,Bob,user
  3,Charlie,user

Method 2: JavaScript Implementation

For comprehensive JavaScript examples with Node.js, Express.js, and production patterns, see our complete JavaScript implementation guide.

npm install @toon-format/toon

const toon = require('@toon-format/toon');

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

// Encode to TOON
const toonString = toon.encode(jsonData);
console.log(toonString);

// Decode back to JSON
const decoded = toon.decode(toonString);
console.log(decoded);

Method 3: Python Implementation

pip install toon-format

from toon_format import encode, decode

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

# Encode to TOON
toon_string = encode(json_data)
print(toon_string)

# Decode back to Python dict
decoded = decode(toon_string)
print(decoded)

Performance Comparison: Speed & Parsing

Parsing Speed

Verdict: JSON is marginally faster, but TOON's overhead is negligible (20µs) compared to token cost savings.

LLM Comprehension Accuracy

Test: 209 data retrieval questions across 4 LLM models

Frequently Asked Questions

Conclusion: Making Your Choice

The choice between TOON, JSON, and YAML depends on your specific use case:

Key Takeaways

• ✅ TOON reduces LLM token usage by 30-60% through intelligent tabular compression
• ✅ TOON improves LLM accuracy (73.9% vs 69.7%) with explicit structure
• ✅ Use TOON for uniform arrays feeding into LLMs (customers, orders, metrics)
• ✅ Keep JSON for mixed data, APIs, and backward compatibility
• ✅ Choose YAML only for human-edited configuration (DevOps, IaC)
• ✅ Easy conversion from JSON to TOON via online tools or libraries

Next Steps

Ready to start optimizing your LLM costs? Here's what to do:

• Try our free JSON to TOON converter - Test with your real data
• How to Convert JSON to TOON - Step-by-step tutorial
• TOON Format Guide - Deep technical dive
• LLM Token Optimization - Complete cost reduction guide
• TOON Documentation - Complete syntax reference
• More TOON Articles - Tutorials and best practices