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Equation 23 · Part 1 · OpenAI Model Systems from First Principles: Weights, Post-Training, and Inference Compute

Symbol q

q(b)q(b)
qq

What this part means

q is a part of this expression. Its role is fixed by the surrounding article and by the operations shown in the formula.

Its job in the formula

q is a part of this expression. Its role is fixed by the surrounding article and by the operations shown in the formula.

The passage around this formula

Consider a task instance with a policy πθ\pi_\theta and a compute budget b spent at inference, whether as sequential deliberation, parallel sampling, or search against a verifier. Expected quality is some q(b) that rises and saturates. Snell and colleagues studied this directly and reported that allocating test-time compute adaptively to the difficulty of the prompt substantially outperforms uniform allocation, and that in some regimes additional inference compute is a more effective use of a marginal FLOP than additional parameters [ 9 ] . The practically important half of that finding is the first: the optimal b is a function of the instance, not of the model.

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Learn the underlying idea

A function assigns an output to each allowed input. The expression f(x) means “apply f to x”.

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