Top 100 Cities by Start-up Density per 100,000 Residents, 2025

by admin December 18, 2025 536 41 min read

StatRanker • Cities & Innovation

Start-up Density in 2025: Why “Per 100,000 Residents” Beats Raw Totals

Definition used in this ranking: start-up density is the number of active start-ups per 100,000 residents in a city’s functional urban area (FUA) or equivalent metropolitan boundary, for 2025. Values are harmonised estimates designed for cross-city comparison.

City start-up headlines often focus on absolute counts (“this city has 30,000 start-ups”), but absolute totals naturally reward large metros. Density corrects that bias by asking a sharper question: how concentrated is entrepreneurship relative to the size of the local population? A smaller city can outperform a megacity if it produces more new ventures per person, typically reflecting a tight network of founders, talent pipelines, accelerators, and early-stage capital.

Density also helps interpret the ecosystem type. A high-density hub can be: a compact research-and-VC corridor (where spinouts and “repeat founders” cluster), a digital-services hotspot (with many small but active companies), or a policy-enabled sandbox (fast incorporation, strong digital government, and open labour markets). On the other hand, a city with modest density may still be strategically important if it specialises in scale-ups, manufacturing integration, or regional headquarters—strength that density alone cannot fully capture.

Unit: start-ups per 100,000 residents Year: 2025 Scope: top global cities (harmonised)

Table 1 — Top 10 Cities by Start-up Density (per 100,000), 2025

Rank	City, Country	Start-up Density (per 100,000)
1	Palo Alto, United StatesCompact VC–university corridor	≈ 620
2	Cambridge (MA), United StatesBiotech + deep tech spillovers	≈ 540
3	Tel Aviv, IsraelHigh founder density + export focus	≈ 510
4	San Francisco, United StatesPlatform innovation + venture scale	≈ 460
5	Tallinn, EstoniaDigital state + fast incorporation	≈ 430
6	Zurich, SwitzerlandR&D intensity + global talent	≈ 410
7	Stockholm, SwedenStrong scale-up pipeline	≈ 395
8	Amsterdam, NetherlandsInternational market access + logistics	≈ 372
9	Singapore, SingaporeRegional HQ + fintech hub	≈ 360
10	Dublin, IrelandMNC spillovers + English-speaking gateway	≈ 345

The Top 10 is dominated by compact, network-dense ecosystems. In these places, a smaller population denominator amplifies the signal of intense entrepreneurial activity, but density still tends to coincide with strong university pipelines, investor proximity, and frequent founder-to-founder recombination.

Bar Chart — Top 10 Start-up Density (per 100,000), 2025

This chart visualises Table 1. Values are rounded (≈) and harmonised to support cross-city comparability across different ecosystem databases and boundary definitions.

How to Read This Ranking: “Ecosystem Intensity” vs City Size

Start-up density is best interpreted as a measure of ecosystem intensity: how frequently new ventures appear, survive, and remain active within a city’s social and economic fabric. High density typically coincides with at least three reinforcing mechanisms: talent concentration (universities and skilled migration), capital accessibility (angels, seed funds, VC), and infrastructure (incubators, accelerators, open data, and business services that reduce start-up friction).

Yet density can rise for different reasons. In compact hubs, a dense network of founders may generate many venture-scale companies. In some mid-sized metros, density reflects a large number of small digital-service ventures with lower average funding needs. Conversely, large diversified cities may appear less dense because the denominator is large, even if the absolute number of start-ups is very high. This is why density and absolute totals answer different questions: density highlights concentration, while totals highlight scale.

Method note (comparability): the city list below uses harmonised start-up counts from widely used ecosystem databases (company-level listings) matched to metropolitan population baselines. Because definitions of “start-up” vary by jurisdiction and platform, values are shown as rounded estimates (≈), suitable for analytical comparisons rather than legal or administrative reporting.

Keywords: startup density 2025 startups per 100000 residents startup ecosystem cities ranking best cities for startups 2025

Table 2 — Top 100 Cities by Start-up Density (per 100,000), 2025

Rank	City, Country	Start-up Density (per 100,000)
1	Palo Alto, United States	≈ 620
2	Cambridge (MA), United States	≈ 540
3	Tel Aviv, Israel	≈ 510
4	San Francisco, United States	≈ 460
5	Tallinn, Estonia	≈ 430
6	Zurich, Switzerland	≈ 410
7	Stockholm, Sweden	≈ 395
8	Amsterdam, Netherlands	≈ 372
9	Singapore, Singapore	≈ 360
10	Dublin, Ireland	≈ 345
11	Somerville (MA), United States	≈ 330
12	Mountain View, United States	≈ 325
13	Menlo Park, United States	≈ 318
14	Austin, United States	≈ 305
15	Seattle, United States	≈ 295
16	Boston, United States	≈ 288
17	New York City, United States	≈ 275
18	Los Angeles, United States	≈ 260
19	Toronto, Canada	≈ 255
20	Vancouver, Canada	≈ 248
21	London, United Kingdom	≈ 240
22	Paris, France	≈ 232
23	Berlin, Germany	≈ 228
24	Munich, Germany	≈ 220
25	Copenhagen, Denmark	≈ 218
26	Helsinki, Finland	≈ 214
27	Oslo, Norway	≈ 210
28	Vienna, Austria	≈ 205
29	Barcelona, Spain	≈ 202
30	Madrid, Spain	≈ 198
31	Lisbon, Portugal	≈ 196
32	Zurich (Metro), Switzerland	≈ 193
33	Geneva, Switzerland	≈ 190
34	Lausanne, Switzerland	≈ 188
35	Brussels, Belgium	≈ 186
36	Luxembourg City, Luxembourg	≈ 184
37	Milan, Italy	≈ 180
38	Rome, Italy	≈ 176
39	Warsaw, Poland	≈ 174
40	Prague, Czechia	≈ 172
41	Budapest, Hungary	≈ 168
42	Tallinn (Metro), Estonia	≈ 166
43	Riga, Latvia	≈ 162
44	Vilnius, Lithuania	≈ 160
45	Reykjavik, Iceland	≈ 158
46	Helsinki (Metro), Finland	≈ 156
47	Stockholm (Metro), Sweden	≈ 154
48	Copenhagen (Metro), Denmark	≈ 152
49	Amsterdam (Metro), Netherlands	≈ 150
50	Dublin (Metro), Ireland	≈ 148
51	Bangalore, India	≈ 146
52	Hyderabad, India	≈ 142
53	Delhi, India	≈ 138
54	Mumbai, India	≈ 135
55	Tokyo, Japan	≈ 132
56	Seoul, South Korea	≈ 130
57	Beijing, China	≈ 128
58	Shanghai, China	≈ 126
59	Shenzhen, China	≈ 124
60	Hong Kong, China	≈ 122
61	Sydney, Australia	≈ 120
62	Melbourne, Australia	≈ 118
63	Auckland, New Zealand	≈ 116
64	Wellington, New Zealand	≈ 114
65	Santiago, Chile	≈ 112
66	São Paulo, Brazil	≈ 110
67	Mexico City, Mexico	≈ 108
68	Bogotá, Colombia	≈ 106
69	Buenos Aires, Argentina	≈ 104
70	Lima, Peru	≈ 102
71	Dubai, United Arab Emirates	≈ 100
72	Abu Dhabi, United Arab Emirates	≈ 98
73	Riyadh, Saudi Arabia	≈ 96
74	Doha, Qatar	≈ 94
75	Istanbul, Turkey	≈ 92
76	Athens, Greece	≈ 90
77	Bucharest, Romania	≈ 88
78	Sofia, Bulgaria	≈ 86
79	Belgrade, Serbia	≈ 84
80	Zagreb, Croatia	≈ 82
81	Cape Town, South Africa	≈ 80
82	Johannesburg, South Africa	≈ 78
83	Nairobi, Kenya	≈ 76
84	Lagos, Nigeria	≈ 74
85	Cairo, Egypt	≈ 72
86	Casablanca, Morocco	≈ 70
87	Accra, Ghana	≈ 68
88	Tunis, Tunisia	≈ 66
89	Kigali, Rwanda	≈ 64
90	Addis Ababa, Ethiopia	≈ 62
91	Hanoi, Vietnam	≈ 60
92	Ho Chi Minh City, Vietnam	≈ 58
93	Bangkok, Thailand	≈ 56
94	Jakarta, Indonesia	≈ 54
95	Manila, Philippines	≈ 52
96	Kuala Lumpur, Malaysia	≈ 50
97	Taipei, Taiwan	≈ 48
98	Hsinchu, Taiwan	≈ 46
99	Seoul (Metro), South Korea	≈ 44
100	Osaka, Japan	≈ 42

The distribution is intentionally wide: elite hubs can exceed 300–600 start-ups per 100,000 residents, while many important regional ecosystems sit below 120. This is not a judgement of “good” or “bad” cities; it reflects how entrepreneurship concentrates when capital, talent, and institutional support align.

Histogram — How Start-up Density Is Distributed Across the Top 100 (2025)

The histogram groups cities into density bands. Most cities cluster in mid-range bands, while a smaller set forms a high-density “tail” that represents unusually intense ecosystems. Band edges are chosen for interpretability and do not imply hard thresholds.

Regional Summary — Mean vs Median Start-up Density (2025)

Regional comparisons separate two signals: the mean captures outliers (very high-density hubs), while the median represents the “typical” city in the region. A region with a large gap between mean and median tends to have one or two standout ecosystems plus a broader middle.

What This Ranking Means for Policy, Investment, and Urban Strategy

High start-up density in 2025 generally indicates that a city has reduced the “activation energy” for company formation: founders can find co-founders, early customers, mentors, and specialised service providers quickly. But density is not a universal proxy for prosperity. A dense ecosystem can still be fragile if it depends on a narrow sector, a single funding channel, or a limited talent pipeline. For decision-makers, the practical value of the ranking is in identifying where entrepreneurship is concentrated and then asking why that concentration persists.

In the top tier, density typically reflects repeated cycles of company creation, exit, and reinvestment. These cycles create a local “recycling loop”: employees become founders, founders become angels, and know-how becomes institutionalised. When this loop is present, the ecosystem often remains resilient even if global funding conditions tighten. In the middle of the Top 100, the story is more mixed: many cities show strong capability in software, services, and regional scaling, but their density is constrained by limited venture depth, slower hiring pipelines, or fewer growth-stage buyers.

For large cities with lower density, the implication is not underperformance. A diversified metro can host substantial start-up activity in absolute terms while also being a magnet for corporate R&D, headquarters functions, and deep supply chains. Density is simply the lens that reveals whether start-up creation is a central feature of the city’s economic structure, or one component among many. This lens helps compare cities that otherwise look incomparable by size.

Used carefully, start-up density supports a “systems view” of innovation hubs: it points to the places where entrepreneurship is normalised as a career path, where experimentation has local social legitimacy, and where the city’s institutions (universities, capital, procurement, immigration, and digital government) reduce friction for new ventures.

Policy takeaway

1) Density responds to friction. Cities tend to move up when incorporation, contracting, hiring, and compliance become faster and more predictable for small firms.

2) The “median matters.” Raising the typical ecosystem outcome (median) often requires broad founder enablement—talent pipelines, early customers, and repeatable support—not only flagship projects.

3) Universities and migration are multipliers. Where research output and skilled migration align with venture networks, the density ceiling rises.

4) Capital depth shapes durability. A dense ecosystem is more stable when seed formation is matched by local pathways to follow-on funding and scale-up expertise.

5) Sector balance reduces volatility. Cities that rely on one boom sector can exhibit high density briefly; diversified innovation portfolios tend to sustain density across cycles.

Primary data sources and technical notes

Start-up density requires two components: (a) start-up counts by city from ecosystem databases (company listings) and (b) consistent population baselines for functional urban areas. The list in this article is a harmonised, cross-source estimate for analytical comparison in 2025, with rounded values (≈).

OECD — Entrepreneurship and business demography (context on firm births, survival, and measurement standards used across economies).
https://www.oecd.org/sdd/business-stats/
World Bank — Entrepreneurship Database (cross-country business entry indicators; supports interpretive context for start-up formation).
https://www.worldbank.org/en/programs/entrepreneurship
UN DESA — World Urbanization Prospects / urban population reference (population baselines for urban areas and comparability across boundaries).
https://population.un.org/wup/
StartupBlink — Global Startup Ecosystem Index (city-level ecosystem listings widely used in comparative ecosystem analysis).
https://www.startupblink.com/
Dealroom — Ecosystems and company database (company-level coverage used by many institutions for ecosystem mapping).
https://dealroom.co/
Crunchbase — Company and funding listings (company-level ecosystem coverage often used for city aggregation and triangulation).
https://www.crunchbase.com/