Comparison
Greedy Decoding vs Top-k
Greedy Decoding and Top-k are both common AI/LLM terms but cover different ideas. Here is a quick side-by-side.
When you would reach for Greedy Decoding
Greedy Decoding comes up when the question is fundamentally about inference.
Asking a model "What is 2+2?" — greedy is fine.
When you would reach for Top-k
Top-k comes up when the question is fundamentally about inference.
top-k = 50: a common default in Hugging Face generation.
Frequently asked
What is the difference between Greedy Decoding and Top-k?
Greedy Decoding: Greedy decoding always picks the single highest-probability next token. It is deterministic, fast, and often dull. Top-k: Top-k restricts token sampling to the k highest-probability tokens, then samples from that set. A simpler alternative to top-p.
When should I use Greedy Decoding vs Top-k?
Greedy Decoding is the right concept when you are focused on inference. Top-k applies when you are focused on inference.
Are Greedy Decoding and Top-k the same thing?
No. Greedy Decoding is inference; Top-k is inference. They are related but address different parts of the AI stack.