What is model pruning (and sparsity), and how does it compare to quantization and distillation?
Pruning strips redundant weights to make a model smaller and sometimes faster. The signal is the structured-versus-unstructured divide and why only structured pruning dependably cuts latency on commodity hardware.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Pruning strips redundant weights to make a model smaller and sometimes faster. The signal is the structured-versus-unstructured divide and why only structured pruning dependably cuts latency on commodity hardware.
Lead with where the obvious approach breaks, because that is the judgment they are screening for — most candidates jump straight to the happy path and lose the room.
Then walk the failure back through the pipeline in order, naming the one metric the customer's exec sponsor actually cares about before you propose the fix.
