Ao vivo
Progresso da IA

O estado do progresso da inteligencia artificial

Computacao, modelos, chips, data centers e benchmarks: a trajetoria completa da IA, quantificada e atualizada continuamente.

Computacao de treino ao longo do tempo

Cada modelo seguido com computacao de treino conhecida, de 1950 a 2026 — 25 ordens de grandeza numa escala logaritmica.

Modelos representados
1,399
Duplicacao na fronteira
5.4 meses
Fronteira
Outros modelos
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
Conjuntos de dados
Vistas transversais
Como estes numeros sao obtidos

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.

Ler a metodologia completa
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.
Ultima sincronizacao 2026-07-29