{"data":{"slug":"gpt-3","etype":"model","name":"GPT-3","cat":"Historical","subtitle":"175 billion parameters and the discovery of in-context learning.","summary":"GPT-3 demonstrated that a large enough language model could perform tasks from a few examples in its prompt — no fine-tuning — launching the API business model and the scaling era. Trained on V100 clusters with 3.1×10²³ FLOP (disclosed), it is the ancestor of every product on this site's Models list.","attrs":[{"b":"Published paper","g":"Overview","l":"Training compute","v":"3.1×10²³ FLOP"},{"b":"Published paper","g":"Overview","l":"Training hardware","v":"NVIDIA V100 clusters (Microsoft-built)"}],"kf":{"params":"175B","context":"2K","weights":"Closed","modality":"Text","rel_date":"2020-06","developer":"OpenAI"},"aliases":["GPT3","davinci"],"ticker":null,"exchange":null,"hq":null,"founded":null,"website":null,"status":"Historical","region":null,"asof":"2026-01-15","sources":[{"url":"https://arxiv.org/abs/2005.14165","label":"GPT-3 paper"}]},"meta":{"found":true,"count":1,"served_from":"site cache (no live upstream calls)","as_of":"2026-10-14T03:49:20+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."}}