JSON to TOON — Reduce LLM API Costs by 30-60% With Token-Optimized Format

If you're feeding JSON into GPT-4, Claude, or Gemini — you're probably wasting tokens on whitespace and verbose keys.

TOON (Token-Optimized Object Notation) is a compact format designed to cut that overhead by 30-60%.

What TOON looks like

Standard JSON (verbose)

{
  "user_identifier": 12345,
  "first_name": "Alice",
  "last_name": "Smith",
  "account_status": "active",
  "subscription_tier": "premium"
}

TOON (compact)

uid:12345|fn:Alice|ln:Smith|status:active|tier:premium

Same data. Fraction of the tokens.

Why this matters for LLM costs

Model	Price	Impact
GPT-4o	~$5/1M input tokens	30-60% savings = significant
Claude Sonnet	~$3/1M input tokens	Same
Gemini 1.5	~$1.25/1M input tokens	Same

If you're processing thousands of records, the savings add up fast.

When to use TOON

• ✅ Sending structured data to LLMs for analysis
• ✅ RAG pipelines with large context windows
• ✅ Batch processing JSON records through AI APIs
• ❌ Not for APIs expecting standard JSON responses
• ❌ Not for human-readable config files

Convert your JSON

Use the free JSON to TOON converter — paste your JSON and get the token-optimized output immediately.

Full comparison with real cost calculations: JSON vs TOON — Complete Guide