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New TOON format halves LLM prompt tokens for JSON arrays

By PulseAugur Editorial · [1 sources] ·

A developer has introduced TOON, a new data format designed to significantly reduce token usage when sending JSON arrays to large language models like GPT and Claude. TOON achieves this by declaring keys only once and then listing values row by row, which can cut token counts by 30-60% for repetitive data. While not suitable for deeply nested or mixed-shape data, this format offers substantial cost savings and context window efficiency for users who frequently input large arrays of similar objects into LLMs. A free online converter and token estimator for TOON is also available. AI

IMPACT Reduces LLM operational costs and increases context window efficiency for users processing large JSON datasets.

RANK_REASON New data format for optimizing LLM prompt efficiency.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New TOON format halves LLM prompt tokens for JSON arrays

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New data format for optimizing LLM prompt efficiency.
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57 days old
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  1. dev.to — LLM tag TIER_1 English(EN) · Wajeeha ·

    TOON: the JSON trick that cut my LLM prompt tokens by half

    <p>I run a small developer tools site, and the whole thing started with one annoyance: sending JSON arrays to GPT or Claude wastes a ridiculous amount of tokens on repeated keys. </p> <p>Look at a typical API response: </p> <p>[ </p> <p>{ "id": 1, "name": "Alice", "role": "admin"…

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