Your INT4-quantized model lost too much accuracy. How do you recover it?
Naive 4-bit quantization can wreck quality, and the reflex to give up and serve fp16 leaves a large speedup unclaimed. The accuracy is usually recoverable. Here is the ladder of fixes.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Naive 4-bit quantization can wreck quality, and the reflex to give up and serve fp16 leaves a large speedup unclaimed. The accuracy is usually recoverable. Here is the ladder of fixes.
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.
