Equation 1 · Part 2 · OpenAI Model Systems from First Principles: Weights, Post-Training, and Inference Compute

Pretraining compute

C_{\mathrm{total}} = C_{\mathrm{pre}} + C_{\mathrm{post}} + Q \cdot \bar{c}_{\mathrm{inf}},

C_{\mathrm{pre}}

What this part means

The one-time computation used to learn from the initial training data.

Its job in the formula

$C_p$ re is one of the signed contributions combined to compute the quantity on the left.

Full expressionPretraining computeArticle meaning

The passage around this formula

Write the total lifetime computation of a deployed system as $C_{\mathrm{total}} = C_{\mathrm{pre}} + C_{\mathrm{post}} + Q \cdot \bar{c}_{\mathrm{inf}}$ . where $C_{\mathrm{pre}}$ is pretraining compute, $C_{\mathrm{post}}$ is post-training compute, Q is the number of served requests over the system’s life, and $\bar{c}_{\mathrm{inf}}$ is the mean compute per request. Until roughly 2024 the third term was treated as approximately fixed for a given model, and…

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A subscript is a label attached below a symbol. It often selects a time step, component, category, or member of a sequence.

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Sources cited in the surrounding passage

[2] Model guidance ↗

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