라이브
AI 진전

인공지능 진전의 현재

연산 능력, 모델, 칩, 데이터센터, 벤치마크 — 인공지능의 전체 궤적을 수치로 담아 지속적으로 갱신합니다.

시간에 따른 학습 연산량

1950년부터 2026년까지 학습 연산량이 알려진 모든 추적 모델. 로그 눈금으로 25자릿수에 걸쳐 있습니다.

표시된 모델
1,399
프런티어 두 배 주기
5.4 개월
프런티어
기타 모델
Largest training run
5×10²⁶ FLOP
Grok 4 · xAI
Tracked data-center power
11.86 GW
across 75 sites
Tracked data-center compute
12.5M H100e
H100 equivalents
Top capability index
161.7
GPT-5.6 Sol (max) · ECI
데이터셋
교차 보기
이 수치가 산출되는 방식

Almost nothing here is disclosed by the labs. Training compute is reconstructed from hardware counts and training time; data-center capacity is inferred from construction permits, satellite imagery and power contracts; chip supply is modelled from earnings and shipment data. So every estimate carries its uncertainty with it — a confidence tag on an attribution, a 5th-to-95th percentile band on a supply figure, a note on how a compute number was derived. Those qualifiers are kept on the page rather than rounded away.

The underlying research is Epoch AI's, published under a Creative Commons Attribution license. What is added here is structure: one durable URL per model, per data center, per cluster, per chip, per benchmark — server-rendered, cross-linked and citable, instead of locked inside an interactive explorer.

전체 방법론 읽기
SourceEpoch AI, 'AI Models'. Published online at epoch.ai. Retrieved 2026-07-29 from https://epoch.ai/data/ai-models. Licensed under CC BY 4.0.
마지막 동기화 2026-07-29