You set temperature to 0 and send the same prompt twice, and the outputs differ. Why, and when does it matter?
Temperature 0 is not the same as deterministic, and the reason lives in the GPU kernels, not the sampler. What gets scored is naming the batch-invariance problem and knowing which fixes are real versus placebo.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Temperature 0 is not the same as deterministic, and the reason lives in the GPU kernels, not the sampler. What gets scored is naming the batch-invariance problem and knowing which fixes are real versus placebo.
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.
