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GPT-6.1 Terra pricing detailed: cost drivers and repricing rules

By PulseAugur Editorial · [1 sources] ·

A detailed breakdown of the pricing for GPT-6.1 Terra reveals that while input tokens are priced low, the actual cost is significantly impacted by factors like reasoning tokens, which are billed as output, and a repricing rule that doubles costs for requests exceeding 272,000 input tokens. Caching mechanisms also add complexity, with prefix writes incurring substantial charges and separate caches for different API routes leading to redundant billing. For a workload of 10,000 requests per month, the estimated cost is $91.25, with output tokens accounting for the majority of this expense. AI

IMPACT Provides clarity on the cost implications of using advanced LLMs, helping developers optimize their usage and budget.

RANK_REASON Detailed pricing breakdown and technical explanation of a specific model's cost structure.

Read on dev.to — LLM tag →

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

GPT-6.1 Terra pricing detailed: cost drivers and repricing rules

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32 / 100
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Detailed pricing breakdown and technical explanation of a specific model's cost structure.
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COVERAGE [1]

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

    GPT-6.1 Terra Cost Breakdown: Effort Tokens, the 272K Repricing Rule and Cache Writes

    <p>A support workload of 10,000 requests a month on GPT-6.1 Terra, run at the model's default medium effort, prices out at <strong>$91.25</strong> on standard rates, cache writes aside. Output tokens are $75 of that, or 82%. The input price that makes Terra look cheap — $1 per mi…

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