Gen AI Interview #11: Greedy Decoding vs Beam Search - How LLMs Choose Their Next Word 2026!

Every time an LLM generates text, it has to make a decision - which token comes next? The strategy it uses to make that decision directly affects output quality, speed, and cost. Greedy decoding and beam search are two of the most fundamental decoding strategies in modern LLM systems, and this is a question asked consistently in AI Engineer and GenAI interviews at FAANG, MNCs, and top AI startups in 2026. We cover what greedy decoding is and why it always picks the most probable next token, how beam search improves output quality by keeping top-k sequences at every step and selecting the best…