Chengdu
Metro Power
66.0
of 100 · #22
MPI
66.0
MCC
46.9
MDI
44.4
Pillar profile
Talent41.2
Capital40.4
Research44.4
Infrastructure64.2
Agentic44.4
Indicators
- Population (m)21.2
- GDP ($bn)320
- GDP per capita ($k)15
- AI investment ($bn)4
- Tech employment %7.5
- AI talent60
- Research strength64
- Notable AI orgs28
- Compute / data centers70
- Broadband %85
- Tertiary degree %36
- Digital skills64
- Startup ecosystem64
- Agent adoption46
- Patents / 100k55
Nearest peers
Metro report · generated from Chengdu's indicators
Chengdu — metro standing in full
Chengdu is the #35 metro by economic size ($320bn) in the panel and ranks #22/162 on absolute Metro Power and #69/162 on per-capita intensity. No pillar stands out as a clear strength; no single pillar is a binding weakness. Locally it runs below the China national average (MCC 46.9 vs CC 69.9).
National context: China scores CC 69.9 per-capita; Chengdu sits at MCC 46.9.
Economic & scale context curated v1 estimate
GDP (metro)
$320bn
#35 of 162
GDP / capita
$15k
Population
21.2M
AI investment
$4.0bn
#57 of 162
Notable AI orgs
28
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Chengdu's own standing.
| Index / pillar | Value | Standing | What a high vs low value means — and where Chengdu sits |
|---|---|---|---|
| MPI Metro Power | 66.0 | Strong · #22/162 | 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 | 46.9 | Moderate · #69/162 | Mid-pack. High would mean deep capability per resident — a concentrated, high-intensity ecosystem; low would mean thin intensity per resident — capability is sparse relative to the population. ▲ 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 | 44.4 | Moderate · #70/162 | Mid-pack. High would mean agents are widely deployed locally — a near-term productivity multiplier; low would mean agentic deployment is shallow — the local agent lever is under-used. ▲ 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 | 41.2 | Moderate · #90/162 | Mid-pack. High would mean a deep talent pool — the scarcest input to building AI; low would mean a shallow talent base that constrains how much can be built locally. ▲ 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 | 40.4 | Moderate · #50/162 | Mid-pack. High would mean abundant capital flowing into building cognitive infrastructure; low would mean thin investment — good ideas struggle to scale locally. ▲ high: abundant capital flowing into building cognitive infrastructure · ▼ low: thin investment — good ideas struggle to scale locally |
| Research Research | 44.4 | Moderate · #64/162 | Mid-pack. High would mean a strong research base feeding a pipeline of ideas and people; low would mean a weak research base — fewer home-grown breakthroughs and spinouts. ▲ 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 | 64.2 | Moderate · #93/162 | Mid-pack. High would mean the physical and digital rails to run AI at scale are in place; low would mean infrastructure gaps cap how much AI can actually be run locally. ▲ 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 | 44.4 | Moderate · #70/162 | Mid-pack. High would mean agents are actively deployed — an early-mover productivity edge; low would mean little agentic deployment — the near-term lever is unused. ▲ high: agents are actively deployed — an early-mover productivity edge · ▼ low: little agentic deployment — the near-term lever is unused |
Strengths to build on
- No pillar stands out as a clear strength yet.
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.