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LLM task costs can double due to retries for valid JSON output

By PulseAugur Editorial · [1 sources] ·

The cost of using LLMs for tasks like JSON extraction can be significantly higher than the base API price due to the need for validation and retries. While API calls are billed per token regardless of output quality, factors like temperature and seed settings influence the success rate of generating usable output. Higher temperatures increase the likelihood of errors, leading to more retries and thus higher overall costs, potentially doubling the price for tasks requiring strict validation. AI

IMPACT LLM users should set temperature to 0 for tasks requiring strict output formats like JSON and utilize structured output modes to minimize retry costs.

RANK_REASON The item discusses the practical cost implications of using LLMs for structured data extraction, focusing on factors beyond the base API pricing.

Read on dev.to — LLM tag →

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

LLM task costs can double due to retries for valid JSON output

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The item discusses the practical cost implications of using LLMs for structured data extraction, focusing on factors beyond the base API pricing.
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · Andrey Altrouter ·

    $667 or $1,100 for the same 100,000 JSON extractions — and the price per token never changed

    <p>Ask what an LLM call costs and you get the price list. Ask what a <em>task</em> costs and the honest answer is the price list divided by how often the answer is usable. That divisor is set by two knobs most beginners copy from a tutorial and never touch again — temperature and…

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