benchmark — A standard public test set for comparing AI models — the shared scoreboards behind every "model X beats model Y" claim.
transformer — The neural network architecture behind modern AI models, built on attention — letting every word directly consider every other word in parallel.
token — The chunk of text a model reads and writes in — roughly three-quarters of a word — and the unit AI usage is billed in.
context window — The maximum amount of text a model can consider at once — its working memory for the current conversation or task.
Why it matters
Hybrid architectures don't beat transformers evenly: the gain sits on content words and tokenThe chunk of text a model reads and writes in — roughly three-quarters of a word — and the unit AI usage is billed in.Full definition → that require following long-range context windowThe maximum amount of text a model can consider at once — its working memory for the current conversation or task.Full definition →, which tells you where the architecture choice actually pays.
