The state of artificial intelligence progress

Training compute, parameters, dataset size, hardware and accessibility for the machine learning systems that define the field, from the 1950s to today.

Compute capacity, electrical power, capital cost and build-out timeline for the biggest AI training and inference sites in the world.

Every known large GPU cluster and AI supercomputer, with its chip count, compute throughput, power draw and the date it came online.

GPUs, TPUs and custom accelerators with their throughput at each precision, memory bandwidth, power draw, process node and price.

The chip types tracked through the AI supply chain, with their compute in H100-equivalents, memory, power and approximate unit cost.

Revenue, valuation, funding, headcount and compute spend for the labs and platforms at the centre of the industry.

Every evaluation tracked, from saturated classics to the frontier tests models still fail — plus the Epoch Capabilities Index that ties them together.