Another paper that so clearly exposes AI’s long-horizon problem. Long-Horizon-Terminal-Bench, where even frontier agents struggle badly once tasks stretch across hundreds of steps. Across 17 frontier models on 46 long terminal tasks, the average pass rate is 6.4%. And under strict full-completion grading 10 of the 17 models solve zero tasks. Of the runs that fail, 79% end with the clock expiring while the agent is still working. Even the best model, at 28.3%, leaves 7 of every 10 tasks unfinished. The models could perform plenty of locally reasonable steps but could not reliably convert hundreds of those steps into a finished result.