As AI systems evolve, especially with the rise of agentic workflows, developers are encountering a new structured format called TOON (Token-Oriented Object Notation). It’s natural to wonder whether TOON can replace JSON, which has been the foundation of data interchange for decades.
The short answer is simple:
No, TOON cannot replace JSON in general-purpose development.
But yes, TOON can outperform JSON inside LLM-focused workflows.
![toon vs json]()
Let’s break down why — with examples.
What Exactly Is TOON?
TOON (Token-Oriented Object Notation) is a compact, human-readable way of representing JSON data. It was created specifically to optimize LLM prompts, reduce token usage, and make structured data easier for AI models to read and generate.
It keeps the same meaning as JSON but removes:
curly braces { }
quotes " "
commas ,
much of the indentation
This leads to 30–60% fewer tokens, making AI interactions cheaper and more efficient.
In simple words:
JSON is for systems.
TOON is for LLMs.
Why TOON Cannot Replace JSON
1. JSON is universally supported
Every modern system supports JSON:
REST APIs
Web & mobile apps
Databases
Cloud services
Logs & configs
TOON does not have such universal tooling.
2. TOON is designed for LLM-facing workflows
TOON shines when:
sending structured data to GPT
reading/writing examples inside prompts
building agent memory
representing large tables compactly
It is not designed for:
3. JSON is easier and more familiar
Developers can instantly understand and parse JSON. As of today, TOON’s structure is simpler for models, but new for humans.
Where TOON is Better Than JSON
1. Passing structured data into LLMs
TOON reduces prompt size while preserving structure.
2. Large uniform tables
TOON's column-based style is perfect for:
3. LLM tool calling / agent workflows
Models make fewer formatting mistakes with TOON than with JSON.
TOON vs JSON: A Quick Comparison
Feature JSON TOON
Purpose Universal data interchange LLM-optimized structured data
Token usage Higher 30–60% lower
Human readability Very high Medium
Ecosystem support Massive Growing
Best use case APIs, config files, storage Prompts, RAG data, agent memory
TOON is not here to replace JSON globally — it simply fills a specific gap in AI developer workflows.
Code Examples
1. Single Object
JSON
{
"name": "Nitin",
"role": "Solution Consultant",
"active": true,
"experienceYears": 14
}
TOON
name: Nitin
role: Solution Consultant
active: true
experienceYears: 14
2. Array of Objects (TOON’s strong area)
JSON
{
"transactions": [
{ "id": 1, "user": "Alice", "amount": 1200.5, "channel": "UPI" },
{ "id": 2, "user": "Bob", "amount": 999.0, "channel": "Wallet" }
]
}
TOON
transactions[2]{id,user,amount,channel}:
1,Alice,1200.5,UPI
2,Bob,999.0,Wallet
This is extremely compact and perfect for feeding thousands of rows to a model.
3. Encoding & Decoding (TypeScript)
import { encode, decode } from "@toon-format/toon";
const data = {
users: [
{ id: 1, name: "Alice", role: "admin" },
{ id: 2, name: "Bob", role: "user" }
]
};
const toonOutput = encode(data);
console.log(toonOutput);
const backToJson = decode(toonOutput);
console.log(backToJson);
![toon-vs-json]()
Final Verdict
TOON will not replace JSON in everyday software development.
JSON remains the backbone of:
APIs
browsers
mobile apps
backend services
configs
databases
But TOON will replace JSON inside LLM workflows.
It is significantly better for:
prompts
structured examples
RAG context
agent state
tool calling
So the right approach is:
Use JSON for your systems. Use TOON for your models.
I want to share Toon’s official git here for your further reference: https://github.com/toon-format