Hangzhou
Metro Power
67.3
of 100 · #18
MPI
67.3
MCC
60.9
MDI
59.0
Pillar profile
Talent55.0
Capital53.4
Research61.6
Infrastructure75.4
Agentic59.0
Indicators
- Population (m)12.2
- GDP ($bn)290
- GDP per capita ($k)24
- AI investment ($bn)8
- Tech employment %11
- AI talent72
- Research strength68
- Notable AI orgs40
- Compute / data centers74
- Broadband %93
- Tertiary degree %44
- Digital skills74
- Startup ecosystem76
- Agent adoption58
- Patents / 100k240
Nearest peers
- Chicago60.3
- Seoul61.5
- Raleigh-Durham60.0
- Cambridge UK60.0
- Paris59.8
Metro report · generated from Hangzhou's indicators
Hangzhou — metro standing in full
Hangzhou is the #38 metro by economic size ($290bn) in the panel and ranks #18/162 on absolute Metro Power and #18/162 on per-capita intensity. Its strongest pillar is Capital (53.4, Strong); no single pillar is a binding weakness. Locally it runs below the China national average (MCC 60.9 vs CC 69.9).
National context: China scores CC 69.9 per-capita; Hangzhou sits at MCC 60.9.
Economic & scale context curated v1 estimate
GDP (metro)
$290bn
#38 of 162
GDP / capita
$24k
Population
12.2M
AI investment
$8.0bn
#25 of 162
Notable AI orgs
40
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Hangzhou's own standing.
| Index / pillar | Value | Standing | What a high vs low value means — and where Hangzhou sits |
|---|---|---|---|
| MPI Metro Power | 67.3 | Strong · #18/162 | High here — a heavyweight hub where capital, talent and AI organizations concentrate — it can anchor an entire national AI ecosystem. ▲ high: a heavyweight hub where capital, talent and AI organizations concentrate — it can anchor an entire national AI ecosystem · ▼ low: limited absolute weight — a smaller node that leans on capacity built in larger hubs |
| MCC Metro Coefficient | 60.9 | Strong · #18/162 | High here — deep capability per resident — a concentrated, high-intensity ecosystem. ▲ high: deep capability per resident — a concentrated, high-intensity ecosystem · ▼ low: thin intensity per resident — capability is sparse relative to the population |
| MDI Metro Agentic | 59.0 | Strong · #17/162 | High here — agents are widely deployed locally — a near-term productivity multiplier. ▲ high: agents are widely deployed locally — a near-term productivity multiplier · ▼ low: agentic deployment is shallow — the local agent lever is under-used |
| Talent Talent | 55.0 | Strong · #30/162 | High here — a deep talent pool — the scarcest input to building AI. ▲ high: a deep talent pool — the scarcest input to building AI · ▼ low: a shallow talent base that constrains how much can be built locally |
| Capital Capital | 53.4 | Strong · #17/162 | High here — abundant capital flowing into building cognitive infrastructure. ▲ high: abundant capital flowing into building cognitive infrastructure · ▼ low: thin investment — good ideas struggle to scale locally |
| Research Research | 61.6 | Strong · #17/162 | High here — a strong research base feeding a pipeline of ideas and people. ▲ high: a strong research base feeding a pipeline of ideas and people · ▼ low: a weak research base — fewer home-grown breakthroughs and spinouts |
| Infrastructure Infrastructure | 75.4 | Strong · #32/162 | High here — the physical and digital rails to run AI at scale are in place. ▲ high: the physical and digital rails to run AI at scale are in place · ▼ low: infrastructure gaps cap how much AI can actually be run locally |
| Agentic Agentic | 59.0 | Strong · #17/162 | High here — agents are actively deployed — an early-mover productivity edge. ▲ high: agents are actively deployed — an early-mover productivity edge · ▼ low: little agentic deployment — the near-term lever is unused |
Strengths to build on
- Capital (53.4, Strong) — abundant capital flowing into building cognitive infrastructure.
- Research (61.6, Strong) — a strong research base feeding a pipeline of ideas and people.
- Agentic (59.0, Strong) — agents are actively deployed — an early-mover productivity edge.
Risk factors
- No acute structural gaps stand out across the metro pillars.
▲
Metro values are curated estimates (v1) on a consistent global scale — not yet measured sub-national data.