We present key data on over 170 AI accelerators, such as graphics processing units (GPUs) and tensor processing units (TPUs), used to develop and deploy machine learning models in the deep learning era.

Huawei plans major gains in AI chip performance by 2030, but US export controls cap its most important scaling levers. Epoch AI estimates Huawei will produce less than 4% as much AI compute as Nvidia in 2026, a share that could be around 1% by 2028 without access to foreign memory.

Our estimates of how much computing power the leading AI developers rent or use, measured in Nvidia H100-equivalents (H100e).

Epoch AI's analysis of trade data finds a pattern consistent with $3B worth of chips smuggled to China via Malaysia. China recorded $3.8B of server imports from Malaysia in 2024–25; Malaysia recorded only $0.6B of exports.

Epoch AI's AI Data Centers explorer now covers an estimated 44% of global AI compute across 86 sites, with a redesigned interface and expanding global coverage.

Our open database of AI Chip sales, using financial reports, company disclosures, and more to estimate compute, power usage, and spending over time for a wide variety of AI chips.

A first look at Epoch AI's data on compute usage across five leading labs.

Our estimates of how much advanced logic wafer capacity, CoWoS packaging, and HBM memory leading AI chip designers consumed.

US GDP growth has been underestimated by about 0.3 percentage points because statistics miss most of Nvidia's US-generated income, a gap that could widen to 2 points by 2028. Epoch AI traces the accounting gap through Nvidia's fabless chip supply chain.

Since 2023, the average dollar spent on AI chips each quarter has yielded about 49% more performance each year in constant 2025 dollars, doubling every 1.7 years as spending shifts to each new chip generation.