Machinepower Index / Dossiers / Czechia
Rank 19–36 across the scoring rules tested. How this is tested
Czechia
Diffusion Advantage — For nations that cannot build the frontier but can use it faster than anyone: import the models and win on deployment, across the state and the economy, with public consent.
How the Score, Potential and bottleneck cost are worked out: methodology.
The three layers
Energy, grids, data centres and silicon — the physical capacity to run models at scale.
Compute tracked by Epoch AI: Czechia hosts 200 H100-equivalents for foreign firms. Hosted compute is shown, not scored.
Models, alignment capability, standards influence and the talent that produces them.
The capacity to wire AI into the state and the economy while holding public consent.
Where the score comes from
| Layer | Sub-dimension | Basis | Score |
|---|---|---|---|
| Watts | Planning & Permitting | Assessed | 5.2 |
| Firm Power Capacity | Dataset | 3.8 | |
| Sovereign Compute | Dataset | 3.3 | |
| Hardware & Silicon Access | Dataset | 5.0 | |
| Weights | Frontier Model Output | Dataset | 3.0 |
| Alignment Capability | Assessed | 5.2 | |
| Regulatory Standing | Dataset | 7.4 | |
| Talent Density | Assessed | 4.5 | |
| Will | Policy Capacity | Dataset | 8.1 |
| Public Sector Adoption | Dataset | 6.9 | |
| Workforce Transition | Dataset | 7.6 | |
| Public Trust | Assessed | 5.2 |
Assessed marks a measurement we judged rather than took from a dataset: 4 of the 12 here.
Sources
Prague's grid is the main bottleneck, and the European Commission lists Czechia among states with connection backlogs.
View source →Named its AI Act authorities on time; no safety statements or safety body.
View source →A cross-check for planning and permitting, which stays assessed: it scores permits and electricity connections for ordinary firms, not grid-scale connections for data centres.
View source →Largest: Škoda's C24.
View source →Stanford does not count Czechia. Estimated from 0.6 million GitHub developers and Oxford Insights' diffusion pillar, averaged with an estimate from LinkedIn's AI talent share (0.83% of members), calibrated on the nations Stanford counts.
View source →Feeds governance and public-sector adoption; policy capacity is listed separately.
View source →Ipsos does not cover it. Mapped to the Ipsos scale through the 28 countries both surveys cover.
View source →Feeds workforce, rescaled across 173 economies.
View source →Fossil, nuclear, hydro and other dispatchable plant; averaged with generation for firm power.
View source →Bottlenecks
These hold Czechia below its Potential. Its two lowest scores cost it the most: frontier model output at 3.0 (part of Weights) and sovereign compute at 3.3 (part of Watts).
Assessment
Czechia has a small but serious computing base — the Karolina supercomputer and Škoda's own cluster — and a grid around Prague that already sets the limit.
The art of the possible
Its industry, from cars to machinery, is where AI pays first. Deploying models across that base, with Karolina as a public resource, beats chasing hyperscale campuses.
Strategic play — Diffusion Advantage
Put AI into factories first, so Czech suppliers adopt it faster than anyone else in German supply chains.
Leverage — the nearest position. No chokepoint, and none near. Its position is as a supplier inside German industry, which follows rather than sets terms.
Open Czechia in the live Index → — every source behind every number, and the comparison tool.