The AI Race
Country and company scorecards on the eight metrics that define the AI race: compute, models, training flops, investment, chips, patents, talent, and data-center power.
Country scorecard - share of globalStanford HAI · WIPO · Synergy
Each country's share of the global total on six measurable AI-race metrics. Darker bar = bigger share.
| Country | Private $ | Models | Talent | Patents | DC capacity | DC power |
|---|
Data-center power capacitySynergy '24
Top countries by total data-center capacity (GW). Compute = power; these are the physical plants where AI gets built.
Data-center electricity useIEA '24
Annual TWh consumed by data centers. 2026 projections shown as lighter bars.
Private AI investment (cumulative 2013–2024)Stanford HAI '25
Notable AI models released (2024)Epoch AI '25
Top AI labs by training computeEpoch AI '25
Flagship-model training compute, log scale. Bigger = more compute thrown at the largest public model.
| Lab | Country | Flagship model | Training FLOPs | Log10(FLOPs) |
|---|
Notable AI models released per year, globalEpoch AI '25
Top-tier AI talent concentrationMacroPolo '23
AI patent share (WIPO 2024)WIPO '24
Data sources + expand