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ModelTerms

Comparison

Encoder vs Encoder-Decoder

Encoder and Encoder-Decoder are both common AI/LLM terms but cover different ideas. Here is a quick side-by-side.

When you would reach for Encoder

Encoder comes up when the question is fundamentally about architecture.

BERT classifying a sentence as positive or negative.

When you would reach for Encoder-Decoder

Encoder-Decoder comes up when the question is fundamentally about architecture.

T5: every NLP task framed as text-to-text.

Frequently asked

What is the difference between Encoder and Encoder-Decoder?

Encoder: An encoder is a transformer module that reads an input sequence and produces a contextualized representation — a vector per token that captures meaning in context. Encoder-Decoder: An encoder-decoder model has a separate encoder that reads the input and a decoder that generates the output, with cross-attention linking them. T5 and the original transformer are encoder-decoders.

When should I use Encoder vs Encoder-Decoder?

Encoder is the right concept when you are focused on architecture. Encoder-Decoder applies when you are focused on architecture.

Are Encoder and Encoder-Decoder the same thing?

No. Encoder is architecture; Encoder-Decoder is architecture. They are related but address different parts of the AI stack.