What actually drives cost and latency when you serve a multimodal model?
An image is not one input, it is a large prompt. Once you internalize that image tokens dominate prefill, the cost levers stop being model choices and start being resolution, tiling, and cache placement.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
An image is not one input, it is a large prompt. Once you internalize that image tokens dominate prefill, the cost levers stop being model choices and start being resolution, tiling, and cache placement.
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.
