JSON to TOON Converter
Convert complex JSON structures into lightweight TOON format to minimize token usage for LLMs and accelerate AI workflows.
100% client-side conversion. Your data never leaves the browser. No uploads, no logs, no servers.
JSON Tokens (Est.)
0
TOON Tokens (Est.)
0
Token Savings
0%
JSON Input
Options & Output
Frequently Asked Questions
TOON (Token-Oriented Object Notation) is a compact data format optimized for large language models. It minimizes redundant characters and structural overhead found in JSON, achieving 30–60% lower token usage without losing readability or structure.
TOON is token-efficient and accurate, maintains the JSON data model for lossless round-trips, includes LLM-friendly guardrails like explicit lengths and headers, has minimal syntax for readability, and supports a multi-language ecosystem (TypeScript, Python, Go, etc.).
Savings typically range from 30% to 60%, depending on the structure of your JSON. Arrays of uniform objects, which are converted to a tabular format, see the highest savings. This converter provides an estimation, but actual savings depend on the specific tokenizer used by the LLM.
For deeply nested or non-uniform data, compact JSON might be smaller. If your data is only semi-uniform, the savings might not be worth it. For pure tabular data, CSV is smaller. For latency-critical applications, you should benchmark TOON against compact JSON to see which is faster for your specific setup.
The best way is to show, not tell. Wrap your TOON data in ```toon code blocks. When asking the LLM to generate TOON, provide the expected header template. Using tab delimiters can further improve token efficiency.
Absolutely. This is a 100% client-side tool. Your data is processed in your browser and is never uploaded to any server. There are no logs and no tracking.
JSON is verbose with lots of brackets, braces, and quotes. TOON uses a more minimalist, YAML-like syntax and a special tabular format for arrays of objects, which significantly reduces the number of tokens.
This converter is currently one-way (JSON to TOON). While a TOON parser could be built to convert back to JSON, the primary purpose of TOON is for efficient use directly in LLM prompts.
Yes. Nested objects and non-uniform arrays are represented in a simplified, YAML-like format. Uniform arrays of objects are converted to a special tabular format for maximum token savings.
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