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Equation 18 · Part 9 · How AI Inference Serving Actually Works

Denominator: 1-α

E[tokens per round]=1−αγ+11−α.\mathbb{E}[\text{tokens per round}] = \frac{1-\alpha^{\gamma+1}}{1-\alpha}.
1−α1-\alpha

What this part means

The complete quantity below the fraction bar; it must be nonzero for this division.

Its job in the formula

1-α is one of the signed contributions combined to compute the quantity on the left.

The passage around this formula

The size of the win has a clean shape. Model the draft’s acceptance probability as α\alpha per token, roughly constant and independent across the γ\gamma tokens proposed in a round — an idealization real traffic does not fully satisfy, but a useful one for seeing the ceiling. The expected number of tokens accepted per verification round is then E[tokens per round]=1−αγ+11−α\mathbb{E}[\text{tokens per round}] = \frac{1-\alpha^{\gamma+1}}{1-\alpha}. This rises with both α\alpha and γ\gamma , but with steeply diminishing returns in γ\gamma for any α\alpha below one: drafting fifty tokens ahead does not buy anywhere near fifty accepted tokens, because the marginal proposal deep into a long draft is unlikely to be exactly what the target would have generated. The bottleneck decode…

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Learn the underlying idea

A fraction a/b means a divided by b. The top number is the numerator; the bottom number is the denominator, and it cannot be zero.

Open the illustrated fractions: division written vertically guide →

Sources cited in the article section

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