Top 100 Countries by Number of Universities in Global Top 1,000 Rankings, 2025 (NationMaster)
Global Top-1,000 University Footprint by Country: Where World-Ranked Institutions Concentrate
Counting how many universities a country places in global “top-tier” rankings is a pragmatic way to proxy its visible research-and-teaching capacity in the international arena. It is not a count of all higher-education institutions, and it is not a definitive measure of system quality. Instead, it captures how many universities in each country clear a common, globally benchmarked threshold and become comparable on metrics such as research output, citations, international presence, and reputation.
This matters because global rankings—despite their limits—tend to track the parts of higher education that are most tightly connected to knowledge-intensive growth: frontier research, doctoral training, high-skill labor supply, and the institutions that anchor innovation ecosystems. In this sense, the distribution of “top-1,000 presence” looks like a map of the exportable knowledge economy.
Table 1 — Top 100 countries by number of universities in global Top 1,000, 2025
Columns: Rank • Country • # Universities
| Rank | Country | # Universities in Top 1,000 |
|---|---|---|
| 1 | United States | 197 |
| 2 | United Kingdom | 90 |
| 3 | China | 71 |
| 4 | Germany | 47 |
| 5 | India | 46 |
| 6 | Japan | 43 |
| 7 | Australia | 36 |
| 8 | France | 36 |
| 9 | Russia | 34 |
| 10 | Spain | 33 |
| 11 | Italy | 33 |
| 12 | South Korea | 32 |
| 13 | Canada | 31 |
| 14 | Netherlands | 23 |
| 15 | Turkey | 23 |
| 16 | Brazil | 22 |
| 17 | Taiwan | 21 |
| 18 | Sweden | 18 |
| 19 | Belgium | 17 |
| 20 | Malaysia | 16 |
| 21 | Poland | 15 |
| 22 | Iran | 15 |
| 23 | Switzerland | 15 |
| 24 | Portugal | 14 |
| 25 | Austria | 14 |
| 26 | Saudi Arabia | 14 |
| 27 | Mexico | 13 |
| 28 | South Africa | 13 |
| 29 | Finland | 9 |
| 30 | Thailand | 12 |
| 31 | New Zealand | 8 |
| 32 | Czechia | 11 |
| 33 | Ireland | 7 |
| 34 | Denmark | 7 |
| 35 | Greece | 10 |
| 36 | Norway | 10 |
| 37 | Argentina | 10 |
| 38 | Hungary | 10 |
| 39 | Egypt | 10 |
| 40 | Chile | 9 |
| 41 | Indonesia | 9 |
| 42 | Pakistan | 9 |
| 43 | United Arab Emirates | 9 |
| 44 | Romania | 8 |
| 45 | Colombia | 8 |
| 46 | Israel | 8 |
| 47 | Ukraine | 8 |
| 48 | Vietnam | 8 |
| 49 | Bangladesh | 8 |
| 50 | Serbia | 7 |
| 51 | Slovakia | 7 |
| 52 | Bulgaria | 7 |
| 53 | Peru | 7 |
| 54 | Kenya | 7 |
| 55 | Morocco | 7 |
| 56 | Philippines | 7 |
| 57 | Croatia | 6 |
| 58 | Tunisia | 6 |
| 59 | Algeria | 6 |
| 60 | Nigeria | 6 |
| 61 | Ghana | 6 |
| 62 | Ethiopia | 6 |
| 63 | Sri Lanka | 6 |
| 64 | Kazakhstan | 6 |
| 65 | Georgia | 2 |
| 66 | Armenia | 2 |
| 67 | Azerbaijan | 3 |
| 68 | Jordan | 3 |
| 69 | Lebanon | 2 |
| 70 | Kuwait | 2 |
| 71 | Oman | 2 |
| 72 | Bahrain | 1 |
| 73 | Nepal | 3 |
| 74 | Myanmar | 5 |
| 75 | Cambodia | 2 |
| 76 | Mongolia | 2 |
| 77 | Uruguay | 2 |
| 78 | Ecuador | 5 |
| 79 | Venezuela | 5 |
| 80 | Costa Rica | 2 |
| 81 | Panama | 2 |
| 82 | Dominican Republic | 2 |
| 83 | Guatemala | 2 |
| 84 | Honduras | 2 |
| 85 | El Salvador | 2 |
| 86 | Bolivia | 2 |
| 87 | Paraguay | 2 |
| 88 | Jamaica | 1 |
| 89 | Trinidad and Tobago | 1 |
| 90 | Cyprus | 1 |
| 91 | Malta | 1 |
| 92 | Hong Kong | 8 |
| 93 | Singapore | 4 |
| 94 | Slovenia | 2 |
| 95 | Estonia | 1 |
| 96 | Latvia | 1 |
| 97 | Iceland | 1 |
| 98 | Luxembourg | 1 |
| 99 | Qatar | 2 |
| 100 | Lithuania | 2 |
Chart 1 — Top 15 countries by # universities in the global Top 1,000, 2025
The chart visualises the same count metric as Table 1 for the Top 15 countries. Values are harmonised for cross-country comparability and may be rounded.
What the distribution suggests: scale effects, per-capita leaders, and the R&D connection
The first table is dominated by large systems: sheer population, the size of the domestic higher-education market, and the breadth of disciplinary coverage make it easier to place many institutions into a global top-tier list. This is why the biggest countries can lead by count even when their average performance per institution differs.
A useful complement is a per-capita normalisation: universities in the Top-1,000 per 10 million residents. It shifts the lens from “how many” to “how dense” the world-ranked university footprint is. This often highlights smaller, research-intensive countries where a relatively compact population supports a high concentration of globally visible institutions.
Table 2 — Top 50 countries by Top-1,000 universities per 10M people, 2025
| Rank | Country | Universities per 10M people |
|---|---|---|
| 1 | Norway | 18.2 |
| 2 | Sweden | 17.1 |
| 3 | Switzerland | 16.7 |
| 4 | Finland | 16.1 |
| 5 | Austria | 15.4 |
| 6 | Croatia | 15.4 |
| 7 | New Zealand | 15.1 |
| 8 | Belgium | 14.4 |
| 9 | Portugal | 13.5 |
| 10 | Australia | 13.3 |
| 11 | United Kingdom | 13.2 |
| 12 | Ireland | 13.2 |
| 13 | Slovakia | 13.0 |
| 14 | Netherlands | 12.8 |
| 15 | Denmark | 11.7 |
| 16 | Czechia | 10.1 |
| 17 | Hungary | 10.4 |
| 18 | Canada | 7.8 |
| 19 | South Korea | 6.3 |
| 20 | Spain | 6.9 |
| 21 | Italy | 5.6 |
| 22 | France | 5.3 |
| 23 | Germany | 5.6 |
| 24 | United States | 5.9 |
| 25 | Japan | 3.5 |
| 26 | Israel | 8.0 |
| 27 | Turkey | 2.7 |
| 28 | Poland | 3.9 |
| 29 | Greece | 9.7 |
| 30 | Romania | 4.2 |
| 31 | Malaysia | 4.7 |
| 32 | Chile | 4.6 |
| 33 | Portugal | 13.5 |
| 34 | Saudi Arabia | 3.8 |
| 35 | Taiwan | 8.9 |
| 36 | Ukraine | 2.1 |
| 37 | Serbia | 10.6 |
| 38 | Peru | 2.1 |
| 39 | Morocco | 1.9 |
| 40 | South Africa | 2.1 |
| 41 | Argentina | 2.2 |
| 42 | Colombia | 1.5 |
| 43 | Mexico | 1.0 |
| 44 | Brazil | 1.0 |
| 45 | India | 0.3 |
| 46 | China | 0.5 |
| 47 | Russia | 2.3 |
| 48 | Japan | 3.5 |
| 49 | United States | 5.9 |
| 50 | Lebanon | 3.6 |
Chart 2 — Universities per 10M vs R&D spending (% of GDP)
Research intensity is a common bridge between university presence and scientific output. A simple way to visualise this link is a scatter plot: countries with higher R&D expenditure (as a share of GDP) often cluster toward higher “Top-1,000 density.” The relationship is not mechanical—governance, language, system structure, and how rankings score teaching vs research all matter— but the co-movement is a recurring pattern in knowledge economies.
Each point is a country. X-axis: R&D expenditure (% of GDP, latest available observation). Y-axis: universities per 10M people (2025 footprint). Values are rounded for readability.
Related education indicators on StatRanker
Interpreting the ranking: what a “Top-1,000 footprint” implies for systems and economies
A large number of globally ranked universities tends to coincide with deep research infrastructure, strong doctoral pipelines, and institutions that can sustain internationally visible output over long time horizons. In national accounts, these effects rarely show up as a single line item; instead, they appear indirectly—in the ability to absorb new technologies, to train high-skill professionals at scale, and to anchor clusters where firms and labs co-locate.
The per-capita view adds a different interpretation: countries with a dense footprint often combine relatively stable funding models, tight integration between universities and national research systems, and concentrated excellence in a subset of disciplines. This can produce outsized visibility even when total population and absolute counts are smaller.
Finally, it is important to treat rankings as an instrument rather than a verdict. QS, THE, and ARWU reward different mixes of reputation, teaching environment, research volume, and citation impact. As a result, two countries can look similar by “number of ranked institutions” yet differ materially in what their universities are strong at (research intensity vs broad teaching capacity, STEM concentration vs system-wide coverage, and so on).
Policy takeaway (high-level implications)
- Counts are scale-sensitive. Large countries can lead by absolute number of ranked universities even if “top-tier density” is moderate.
- Per-capita density highlights system design. Smaller countries can be highly visible when research and higher education are tightly coordinated.
- R&D intensity often co-moves with density. Higher R&D spending is frequently associated with a stronger presence of globally ranked institutions.
- Ranking systems are not interchangeable. Differences across QS/THE/ARWU can shift which institutions cross a “Top-1,000” threshold.
- Best use-case is comparative structure. The most reliable signal is how countries cluster and how gaps change over time, not single-country point estimates.
Primary data sources and technical notes
- QS World University Rankings 2025 Official ranking edition used to benchmark international representation and to contextualise which systems are most represented among globally ranked institutions. https://www.topuniversities.com/world-university-rankings/2025
- Times Higher Education — World University Rankings methodology Methodology documentation explaining the pillars and indicators used by THE (teaching, research environment, research quality, international outlook, industry). https://www.timeshighereducation.com/world-university-rankings/methodology
- ARWU (ShanghaiRanking) — Methodology (2025) Official ARWU methodology describing how candidate universities are selected and how the best 1,000 are published. https://www.shanghairanking.com/methodology/arwu/2025
- World Bank (WDI) — Research & development expenditure (% of GDP) Indicator definition and cross-country dataset used for the R&D intensity axis in the scatter chart (latest available year varies by country). https://data.worldbank.org/indicator/GB.XPD.RSDV.GD.ZS
- World Bank (WDI) — Population, total Population series used to normalise counts into “universities per 10 million people” for the per-capita table. https://data.worldbank.org/indicator/SP.POP.TOTL
- NationMaster — Education / Universities (historical country comparison pages) Aggregator-style country comparison pages illustrating how ranking-based university counts have been presented in cross-country form. https://www.nationmaster.com/country-info/stats/Education/Universities/Top-200
Download data package: Top 100 Countries by Universities in Global Top 1,000 (2025)
Tables (CSV/XLSX) and chart images (PNG) used in this article.
