{"data":{"slug":"parameters","etype":"concept","name":"Parameters","cat":"Core Technical","subtitle":"The learned numbers — and why 'bigger' stopped being the whole story.","summary":"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.'","attrs":null,"kf":null,"aliases":["weights","parameter count"],"ticker":null,"exchange":null,"hq":null,"founded":null,"website":null,"status":null,"region":null,"asof":"2026-01-15","sources":[{"url":"https://arxiv.org/abs/2203.15556","label":"Chinchilla paper"}]},"meta":{"found":true,"count":1,"served_from":"site cache (no live upstream calls)","as_of":"2026-10-14T03:56:34+00:00","disclaimer":"Research and information only — not investment advice. Structured records carry basis labels (vendor spec / reported / estimate); market quotes are delayed/indicative.","attribution":"Records compiled from vendor documentation, official filings and reputable public reporting; market quotes via financial data providers. See /data-sources."}}