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Self-hosting LLMs: GPU rental vs. per-token API cost calculator

By PulseAugur Editorial · [1 sources] ·

Self-hosting a large language model on a rented GPU becomes more cost-effective than using a per-token API only when the GPU is utilized at a high throughput. The break-even point is calculated by dividing the hourly GPU rental cost by the blended price per token, determining the number of tokens that must be generated per hour to justify the GPU expense. This article provides the formula and a worked example using the Qwen3 32B model on an RTX 5090 32G GPU, highlighting that consistent, high-volume traffic is necessary for self-hosting to be cheaper. AI

IMPACT Provides a framework for developers to calculate the cost-effectiveness of self-hosting LLMs versus using APIs based on usage volume.

RANK_REASON Article provides a calculator and formula for cost comparison of self-hosting an LLM versus using a per-token API.

Read on dev.to — LLM tag →

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

Self-hosting LLMs: GPU rental vs. per-token API cost calculator

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27 / 100
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Tool
Article provides a calculator and formula for cost comparison of self-hosting an LLM versus using a per-token API.
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Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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infra, product
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High
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Breaking (< 6h)
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COVERAGE [1]

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

    Self-Host an LLM on a Rented GPU or Pay per Token? A Break-Even Calculator (2026)

    <p><strong>Self-hosting on a rented GPU is cheaper than a per-token API only when you keep the GPU busy: the break-even is the hourly GPU price divided by the API’s price per token, expressed as tokens you must actually generate and process every hour.</strong> Below that throu…

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