A benchmarking study tested 25 quantitative models against a passive equal-weight baseline strategy across 48 large-cap US stocks from 2022-2025, finding that none achieved statistically significant outperformance after accounting for trading costs. The analysis reveals that high gross returns are often consumed by transaction fees, and that foundation models and neural networks exhibit the same cost-driven underperformance as simpler approaches.