Parameters
The learned numbers — and why 'bigger' stopped being the whole story.
Estás viendo un explicador de concepto: qué significa este término en lenguaje claro, y los registros que conecta.
Parameters are the weights a model learns; storing and moving them is what all the memory on this site is for (a 405B-parameter model needs ~800 GB at 16-bit). Counts climbed from GPT-2's 1.5B to trillion-parameter mixtures, but since Chinchilla the field optimizes parameters against data and compute jointly — and closed labs stopped disclosing counts at all, which is why so many records here say 'not publicly disclosed.'
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Fuentes
Registro revisado a fecha de 2026-01-15 — ver Metodología.