Machinepower Index / Dossiers / Pakistan
Rank 45–49 across the scoring rules tested. How this is tested
Pakistan
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.
Epoch AI records no large AI clusters or data centres here yet.
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 | 4.0 |
| Firm Power Capacity | Dataset | 4.9 | |
| Sovereign Compute | Assessed | 2.0 | |
| Hardware & Silicon Access | Dataset | 2.0 | |
| Weights | Frontier Model Output | Dataset | 3.0 |
| Alignment Capability | Assessed | 3.0 | |
| Regulatory Standing | Dataset | 6.1 | |
| Talent Density | Assessed | 4.5 | |
| Will | Policy Capacity | Dataset | 6.2 |
| Public Sector Adoption | Dataset | 3.7 | |
| Workforce Transition | Dataset | 4.2 | |
| Public Trust | Assessed | 7.6 |
Assessed marks a measurement we judged rather than took from a dataset: 5 of the 12 here.
Sources
2,000 MW of spare generation was offered to data centres and crypto mining in 2025, but distribution is unreliable.
View source →A 2025 national AI policy but none of the international AI commitments; no 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 →No system on the June 2026 TOP500 and no compute controlled by the state, universities or firms in Epoch AI; set at the floor.
View source →Stanford does not count Pakistan. Estimated from 2.5 million GitHub developers and Oxford Insights' diffusion pillar, calibrated on the nations Stanford counts.
View source →Feeds governance and public-sector adoption; policy capacity is listed separately.
View source →No AI survey in the last three years covers it; set at the median of the 15 surveyed emerging and developing economies in the Index.
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 Pakistan below its Potential. Its two lowest scores cost it the most: sovereign compute at 2.0 (part of Watts) and hardware & silicon access at 2.0 (part of Watts).
Assessment
Pakistan has two and a half million developers and spare generating capacity it has offered to data centres, but distribution is unreliable and the state's own use of AI is low.
The art of the possible
Its freelance and software-export workforce is the asset. Putting spare power behind compute for those firms would add more than waiting for foreign campuses.
Strategic play — Diffusion Advantage
Back the freelancers: put spare power and imported models behind Pakistani software firms.
Leverage — the nearest position. No chokepoint. Its position is a large, low-cost technical workforce, which others hire but can replace.
Open Pakistan in the live Index → — every source behind every number, and the comparison tool.