Scaling dimension refers to the architectural choice of where to add capacity — more layers (depth), wider layers (width), more attention heads, longer context, or more experts — each with different compute and quality trade-offs. Scaling laws research shows these dimensions are not interchangeable: depth improves reasoning, width improves memorization, and experts improve efficiency at a given compute budget.