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Equation 6 · Part 9 · Context Window Size Versus What a Frontier Model Can Actually Recall From It

≥

Leff(τ)=max⁡{ n≤W : S(n)≥τ⋅S0 }L_{\mathrm{eff}}(\tau) = \max\left\{\, n \le W \ :\ S(n) \ge \tau \cdot S_0 \,\right\}
≥

What this part means

Greater than or equal to.

Its job in the formula

Greater than or equal to.

The passage around this formula

Put the documentation and the independent benchmarks side by side and a pattern emerges that is more informative than any single score. Formalise the distinction the whole comparison rests on: let W be the context window a vendor documents for a given model, a fixed engineering figure set by attention implementation, position encoding, and what the serving stack supports. Let S(n) be some benchmark’s measured accuracy at input length n ≤\le W , and S0S_0 the same benchmark’s accuracy at a short reference length. For a chosen retention threshold τ\tau , define the effective context length as Leff(τ)=max⁡{ n≤W : S(n)≥τ⋅S0 }L_{\mathrm{eff}}(\tau) = \max\left\{\, n \le W \ :\ S(n) \ge \tau \cdot S_0 \,\right\}. W is a documented constant, published on day one of a model’s release, identical no…

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An inequality compares values without claiming they are equal. It describes a range, threshold, or bound that a quantity may satisfy.

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Sources cited in the article section

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