{"data":{"slug":"test-time-compute","etype":"concept","name":"Test-time Compute & Reasoning","cat":"Training & Inference","subtitle":"The 2024 discovery: models get smarter by thinking longer.","summary":"Reasoning models produce long internal chains of thought before answering, and accuracy scales with how much compute they spend thinking — a new scaling axis alongside model size and data. o1 introduced it; R1 open-sourced it; every frontier model now has a thinking mode. The infrastructure consequence is enormous: a single hard question can cost thousands of times more tokens than a chat reply, shifting demand from training clusters to inference fleets.","attrs":null,"kf":null,"aliases":["reasoning models","chain of thought","thinking mode"],"ticker":null,"exchange":null,"hq":null,"founded":null,"website":null,"status":null,"region":null,"asof":"2026-01-15","sources":[{"url":"https://openai.com/index/learning-to-reason-with-llms/","label":"Learning to reason (OpenAI)"}]},"meta":{"found":true,"count":1,"served_from":"site cache (no live upstream calls)","as_of":"2026-10-14T06:50:19+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."}}