The organization-level capability gap on the Artificial Analysis (AA) Intelligence Index is currently tight, with the gap between the top organization (~63) and the runner-up (~61) at about 2 points 2 sources. Reconstructing the contemporaneous organization-level gaps across 2024–2026 yields a historical mean denominator of roughly 2.5 points. Consequently, simply maintaining today's heavily contested status quo through late 2028 would result in a ratio of approximately 0.8. However, evaluating this alongside forecasts of capability diffusion to balance the likelihood of continued benchmark compression against the risk of sudden leapfrog releases by incumbents firmly anchors the median at 0.85. Structural forces heavily favor continued compression. Algorithmic efficiency improves by roughly 3x per year epoch.ai, and open-weight models trail the closed frontier closely 2 sources. Furthermore, benchmark saturation mechanically compresses index spreads. While the continual learning flywheel could theoretically widen the gap dwarkesh.com, the deployment-to-weights mechanism is not yet operating at frontier scale. Live "memory" heavily relies on retrieval rather than live weight updates 2 sources. The forecast distribution is wide—spanning from 0.2 at the 10th percentile to 2.25 at the 90th percentile—and right-skewed due to the mechanics of single-day measurement. A snapshot on December 31, 2028, is highly susceptible to release timing, potentially capturing a dead heat or the immediate aftermath of a leapfrog release.