2026-10-05 02:22:02
Fifteen years ago, the global smartphone market looked almost unrecognizable by today’s standards. Nokia was the world’s largest smartphone maker, BlackBerry ranked second, and Apple was in third place.
This visualization compares the five largest smartphone companies by worldwide shipments in 2010 and 2025, showing how dramatically the industry’s leading players have changed.
The data comes from the IDC Worldwide Quarterly Mobile Phone Tracker. Figures represent worldwide shipments of new smartphones, with 2025 figures considered preliminary.
Global smartphone shipments rose from 302.6 million units in 2010 to 1.26 billion in 2025, making the market roughly four times larger in 15 years.
That growth was accompanied by a major reshuffling of the companies at the top.
| Rank | Company | Shipments (2010) | Market share |
|---|---|---|---|
| 1 |
Nokia |
100.2M | 33.1% |
| 2 |
RIM (BlackBerry) |
48.7M | 16.1% |
| 3 |
Apple |
47.5M | 15.7% |
| 4 |
Samsung |
23.0M | 7.6% |
| 5 |
HTC |
21.5M | 7.1% |
| Rank | Company | Shipments (2025) | Market share |
|---|---|---|---|
| 1 |
Apple |
247.8M | 19.7% |
| 2 |
Samsung |
241.2M | 19.1% |
| 3 |
Xiaomi |
165.3M | 13.1% |
| 4 |
vivo |
103.9M | 8.2% |
| 5 |
OPPO |
102.0M | 8.1% |
Apple and Samsung are the only members of the 2010 top five still in the ranking. Apple moved from third to first over the period, while Samsung climbed from fourth to second.
Their shipment volumes also grew substantially. Apple went from 47.5 million smartphones in 2010 to 247.8 million in 2025, while Samsung rose from 23.0 million to 241.2 million.
As smartphone production data from the past decade shows, both companies have remained near the top even as the competitive landscape around them changed.
The contrast with Nokia is particularly stark. The Finnish company held 33.1% of the smartphone market in 2010 but no longer ranks among the world’s five largest vendors.
No Chinese company ranked among the world’s five largest smartphone makers in 2010. By 2025, Xiaomi, vivo, and OPPO occupied third through fifth place and collectively accounted for 29.4% of worldwide shipments.
Xiaomi’s trajectory is particularly notable. The company was founded in 2010, the first year shown in this comparison, and released its first smartphone in 2011. By 2025, it ranked third globally with 165.3 million shipments and a 13.1% market share.
The five leaders controlled 79.6% of global shipments in 2010. In 2025, their combined share fell to 68.2%.
At the same time, the “Others” category grew from 61.7 million smartphones to 400 million, increasing its share of global shipments from 20.4% to 31.7%. The smartphone market is far larger than it was in 2010, while a greater share of shipments now comes from companies outside the five largest vendors.
If you enjoyed this visualization, check out Ranked: The 15 Best-Selling Mobile Phones of All Time on the Voronoi app.
2026-10-05 00:46:07
Who can vote in a U.S. midterm election and who actually shows up are two very different groups.
In 2022, Americans under 45 made up 44.2% of the citizen voting-age population, but just 33.8% of reported voters. Meanwhile, Americans 45 and older accounted for 55.8% of eligible citizens but 66.3% of those who voted.
The data comes from the U.S. Census Bureau’s Current Population Survey, using the most recent completed midterm election, in 2022. It shows how turnout reshapes the age profile of the electorate before votes for individual candidates are considered.
The biggest gap was among the youngest voters. Americans ages 18–24 represented 11.5% of eligible citizens in 2022, but only 6.1% of reported voters.
The pattern flips among older Americans. Those ages 65–74 represented 14.1% of eligible citizens but 18.4% of voters, while Americans 75 and older increased from 9.7% to 12.1%.
| Age bracket | Share of eligible population (CVAP) | Share of voters | Turnout rate |
|---|---|---|---|
| 18-24 | 11.5% | 6.1% | 27.6% |
| 25-44 | 32.7% | 27.7% | 44.3% |
| 45-64 | 32.1% | 35.8% | 58.3% |
| 65-74 | 14.1% | 18.4% | 68.0% |
| 75+ | 9.7% | 12.1% | 65.2% |
Eligible population refers to the citizen voting-age population (CVAP), which excludes minors and non-citizens. Figures are based on reported voting in the November 2022 midterm elections.
Turnout explains much of this shift. Voter turnout was 27.6% among Americans ages 18–24 in 2022, compared with 44.3% among those ages 25–44 and 58.3% among those ages 45–64.
Turnout peaked at 68.0% among Americans ages 65–74 before dipping slightly to 65.2% among those 75 and older.
Older voters also tend to be more engaged with midterm elections. Ahead of the 2022 election, Pew Research Center found that 50% of registered voters ages 65 and older had given the election “a lot” of thought, compared with just 20% of those under 30.
Turnout by age can also affect the composition of the electorate because voting preferences differ substantially across age groups.
In a separate analysis of validated voters in the 2022 midterms, Pew Research Center found that 68% of voters under 30 supported Democratic House candidates, compared with 31% who supported Republicans. Among voters 65 and older, 56% supported Republican candidates and 42% supported Democrats.
These differences also reflect broader generational divides in U.S. politics. There are varying degrees of political affiliation across generations, from Gen Z to the Silent Generation.
Despite the age gap in turnout, today’s youngest voters were more engaged in their first midterm than Millennials and Gen X were at the same stage.
The 2022 election was the first midterm in which Gen Z made up the entire 18–24 age group. CIRCLE found that 28.4% of Gen Z voters in this age group turned out, compared with 23.0% of Millennials in 2006 and 23.5% of Gen X in 1990, when each generation first fully occupied the same age bracket.
In other words, low youth turnout is not unique to Gen Z. Americans in their late teens and early 20s still vote at much lower rates than older adults, but Gen Z participated more in its first midterm than Millennials or Gen X did at the same age.
If you enjoyed today’s post, check out Top 15 Ranked: America’s Reddest and Bluest Cities Based on County on Voronoi, the app from Visual Capitalist.
2026-10-04 22:14:00
Americans have a serious appetite for ice cream, consuming roughly 19 pounds, or about four gallons, per person each year. As of April 2026, the U.S. ice cream industry generates around $7.5 billion in annual sales.
Vanilla remains the most popular flavor nationwide, but this map asks a different question: Which flavors stand out most in each state?
Rather than simply showing the most-ordered flavor, the map highlights the ice cream flavor that over-indexes most in each state compared with the national average.
The data for this visualization comes from Instacart. It is based on ice cream purchases made through the platform in 2025. Some retailers were excluded where required by state law.
Vanilla’s strongest footprint stretches across the Plains and parts of the South, including Texas, Kansas, Nebraska, Alabama, and Mississippi.
Its showing is particularly notable because the analysis adjusts for how frequently each flavor is ordered nationwide.
| State | Signature Ice Cream Flavor |
|---|---|
| Alabama | Vanilla |
| Alaska | Vanilla |
| Arizona | Rocky Road |
| Arkansas | Vanilla |
| California | Rocky Road |
| Colorado | Cherry |
| Connecticut | Peanut Butter |
| Delaware | Mint Chocolate Chip |
| Florida | Chocolate |
| Georgia | Butter Pecan |
| Hawaii | Coffee |
| Idaho | Vanilla |
| Illinois | Vanilla |
| Indiana | Cookie Dough |
| Iowa | Vanilla |
| Kansas | Vanilla |
| Kentucky | Raspberry |
| Louisiana | Vanilla |
| Maine | Coffee |
| Maryland | Vanilla |
| Massachusetts | Coffee |
| Michigan | Cookie Dough |
| Minnesota | Vanilla |
| Mississippi | Vanilla |
| Missouri | Vanilla |
| Montana | Vanilla |
| Nebraska | Vanilla |
| Nevada | Rocky Road |
| New Hampshire | Coffee |
| New Jersey | Mint Chocolate Chip |
| New Mexico | Coffee |
| New York | Peanut Butter |
| North Carolina | Butter Pecan |
| North Dakota | Vanilla |
| Ohio | Peanut Butter |
| Oklahoma | Vanilla |
| Oregon | Coffee |
| Pennsylvania | Mint Chocolate Chip |
| Rhode Island | Coffee |
| South Carolina | Butter Pecan |
| South Dakota | Vanilla |
| Tennessee | Cheesecake |
| Texas | Vanilla |
| Utah | Rocky Road |
| Vermont | Chocolate Fudge/Brownie |
| Virginia | Vanilla |
| Washington | Rocky Road |
| West Virginia | Peanut Butter |
| Wisconsin | Moose Tracks |
| Wyoming | Cherry |
Beyond Vanilla, several flavors form clear geographic clusters.
Rocky Road stands out in five western states, including California, Arizona, Nevada, Utah, and Washington, while Coffee over-indexes in seven states and has an especially strong presence across New England.
In the Southeast, Butter Pecan connects Georgia, North Carolina, and South Carolina. Mint Chocolate Chip forms a Mid-Atlantic cluster across Delaware, New Jersey, and Pennsylvania.
Peanut Butter also has a strong eastern presence, standing out in Connecticut, New York, Ohio, and West Virginia.
A handful of states have signature flavors found nowhere else on the map.
Tennessee is the only state where Cheesecake stands out as the signature flavor. Kentucky is similarly unique with Raspberry, while Vermont is the lone state where Chocolate Fudge/Brownie takes the top spot.
Florida offers another unusual result. Chocolate stands out most there even though it is already the second-most ordered flavor nationally, making Florida’s result notable even after accounting for its broad popularity.
Wisconsin also stands apart. Moose Tracks, a combination of vanilla ice cream, fudge, and peanut butter cups, is the only branded flavor to emerge as a state signature.
Flavor preferences are not the only part of America’s ice cream landscape with a strong regional pattern. Instacart’s data also reveals major differences in the brands states favor.
Häagen-Dazs ranks as the top ice cream brand nationally, with Ben & Jerry’s close behind.
Breyers ranks third, followed by a mix of national and regional favorites. Tillamook, Halo Top, Turkey Hill, and Blue Bell also appear among the leading brands, highlighting the role of both premium positioning and regional loyalty.
Measured by which brand each state favors most compared with the country overall, the results reveal another layer of America’s regional ice cream preferences.
Tillamook has the broadest footprint, standing out across a dozen western states. Blue Bell is strongest across much of the South, while Blue Bunny over-indexes throughout the Great Plains. In New England, Friendly’s maintains a distinctly local following, reflecting the staying power of long-established regional brands.
If you enjoyed today’s post, check out Which Fast Food Chains Offer The Best Value Burgers? on Voronoi.
2026-10-04 20:04:15
Mount Everest is seeing more human traffic than at any point in the last three decades of available data.
Successful climbs are now overwhelmingly concentrated in the spring, when favorable weather can funnel hundreds of climbers toward the summit within a matter of days. Meanwhile, the workforce supporting expeditions has grown alongside the number of people attempting the mountain.
The data comes from The Himalayan Database, which tracks registered expeditions across the Nepal Himalaya. It shows how the scale, timing, and composition of Everest climbing have transformed since the 1990s.
The number of people recorded on Everest has surged alongside the number reaching the summit.
In 2025, The Himalayan Database recorded 585 visitors and 934 hired workers on the mountain, for a total of 1,519 people. That’s nearly four times the 395 people recorded in 1995.
| Year | Visitors on the mountain | Workers on the mountain | Total |
|---|---|---|---|
| 1995 | 247 | 148 | 395 |
| 1996 | 338 | 194 | 532 |
| 1997 | 337 | 198 | 535 |
| 1998 | 271 | 160 | 431 |
| 1999 | 221 | 131 | 352 |
| 2000 | 406 | 247 | 653 |
| 2001 | 371 | 230 | 601 |
| 2002 | 237 | 192 | 429 |
| 2003 | 491 | 352 | 843 |
| 2004 | 394 | 269 | 663 |
| 2005 | 480 | 394 | 874 |
| 2006 | 492 | 392 | 884 |
| 2007 | 595 | 505 | 1,100 |
| 2008 | 402 | 314 | 716 |
| 2009 | 492 | 404 | 896 |
| 2010 | 466 | 444 | 910 |
| 2011 | 458 | 491 | 949 |
| 2012 | 521 | 513 | 1,034 |
| 2013 | 492 | 554 | 1,046 |
| 2014 | 403 | 300 | 703 |
| 2015 | 519 | 444 | 963 |
| 2016 | 454 | 481 | 935 |
| 2017 | 545 | 557 | 1,102 |
| 2018 | 573 | 664 | 1,237 |
| 2019 | 584 | 682 | 1,266 |
| 2020 | 32 | 28 | 60 |
| 2021 | 458 | 588 | 1,046 |
| 2022 | 395 | 636 | 1,031 |
| 2023 | 513 | 737 | 1,250 |
| 2024 | 493 | 789 | 1,282 |
| 2025 | 585 | 934 | 1,519 |
Visitors include clients and independent climbers, while workers are hired expedition staff, most of whom are Nepali Sherpas.
Of those on the mountain in 2025, 878 reached the summit. Across 2021–2025, Everest averaged about 720 summits per year, more than seven times the annual average of roughly 100 in 1995–1999.
Decades ago, successful Everest climbs were spread much more widely across the calendar. In the 1980s, The Himalayan Database recorded 87 spring summits and 77 autumn summits, along with successful climbs in both winter and summer. That pattern has almost completely disappeared.
| Period | Spring | Autumn | Winter | Summer |
|---|---|---|---|---|
| 1980-1989 | 87 | 77 | 9 | 9 |
| 1990-1999 | 739 | 135 | 6 | 0 |
| 2000-2009 | 3,346 | 30 | 0 | 0 |
| 2010-2019 | 5,561 | 6 | 0 | 0 |
| 2020-2025 | 3,634 | 14 | 0 | 0 |
From 2000 through 2009, more than 99% of recorded summits occurred in spring. The concentration became even more extreme in the 2010s, when the database recorded 5,561 spring summits compared with just six in autumn and none in winter or summer.
Since 2020, the pattern has remained virtually unchanged.
Even within the spring season, summit attempts cluster around short periods of favorable weather, particularly in May.
This can create extraordinary spikes in traffic near the top of the mountain.
| Year | Total summits |
|---|---|
| 1995 | 82 |
| 1996 | 98 |
| 1997 | 85 |
| 1998 | 119 |
| 1999 | 116 |
| 2000 | 145 |
| 2001 | 182 |
| 2002 | 158 |
| 2003 | 264 |
| 2004 | 335 |
| 2005 | 307 |
| 2006 | 483 |
| 2007 | 611 |
| 2008 | 428 |
| 2009 | 463 |
| 2010 | 532 |
| 2011 | 541 |
| 2012 | 574 |
| 2013 | 680 |
| 2014 | 133 |
| 2015 | 0 |
| 2016 | 678 |
| 2017 | 680 |
| 2018 | 850 |
| 2019 | 899 |
| 2020 | 49 |
| 2021 | 462 |
| 2022 | 704 |
| 2023 | 685 |
| 2024 | 870 |
| 2025 | 878 |
On May 23, 2019, 354 people reached Everest’s summit from Nepal and Tibet combined, the highest single-day total in the dataset.
These traffic spikes are largely driven by Everest’s extreme weather. Summit attempts typically occur when the jet stream shifts away from the mountain, creating periods of lower winds before the summer monsoon arrives.
As a result, hundreds of climbers who have spent weeks acclimatizing can converge on the upper mountain during the same handful of favorable days.
The growth of Everest climbing has also transformed who is on the mountain. In 1995, The Himalayan Database recorded about three hired workers for every five visitors.
By 2025, there were roughly eight hired workers for every five visitors, with hired workers accounting for more than 60% of all people recorded on Everest that year.
Long before most clients attempt the summit, high-altitude workers carry supplies, stock camps, and help prepare the route. Commercial expeditions also rely on guides and other staff to support climbers during weeks of acclimatization and the final summit push.
The risks faced by that workforce became especially visible during two catastrophic seasons. In 2014, all 17 deaths recorded in the database were hired workers. In 2015, when the Nepal earthquake triggered a deadly avalanche at Everest Base Camp, workers accounted for 11 of the 14 deaths recorded on registered expeditions.
| Year | Total deaths | Visitor deaths | Worker deaths |
|---|---|---|---|
| 1995 | 4 | 1 | 3 |
| 1996 | 15 | 12 | 3 |
| 1997 | 9 | 6 | 3 |
| 1998 | 4 | 4 | 0 |
| 1999 | 4 | 4 | 0 |
| 2000 | 2 | 2 | 0 |
| 2001 | 5 | 4 | 1 |
| 2002 | 3 | 3 | 0 |
| 2003 | 4 | 3 | 1 |
| 2004 | 7 | 7 | 0 |
| 2005 | 6 | 6 | 0 |
| 2006 | 11 | 7 | 4 |
| 2007 | 7 | 6 | 1 |
| 2008 | 1 | 1 | 0 |
| 2009 | 5 | 3 | 2 |
| 2010 | 3 | 3 | 0 |
| 2011 | 4 | 4 | 0 |
| 2012 | 10 | 7 | 3 |
| 2013 | 8 | 4 | 4 |
| 2014 | 17 | 0 | 17 |
| 2015 | 14 | 3 | 11 |
| 2016 | 5 | 5 | 0 |
| 2017 | 6 | 5 | 1 |
| 2018 | 5 | 2 | 3 |
| 2019 | 11 | 10 | 1 |
| 2020 | 0 | 0 | 0 |
| 2021 | 5 | 2 | 3 |
| 2022 | 3 | 2 | 1 |
| 2023 | 18 | 12 | 6 |
| 2024 | 8 | 6 | 2 |
| 2025 | 4 | 2 | 2 |
These were exceptional disaster years rather than typical seasons, but they underscore the occupational hazards faced by the workforce supporting Everest expeditions.
More people on Everest also means more waste to manage. Nepal requires expeditions to remove waste, but doing so at extreme altitude is difficult and expensive.
In spring 2024, the Sagarmatha Pollution Control Committee collected 85 tonnes of waste from Everest Base Camp and higher camps, including 27.53 tonnes of human waste.
Everest is also a major source of income for Nepal. In 2025, the country increased the spring climbing permit fee for foreign climbers from $11,000 to $15,000, with the new rate taking effect in September.
Climbers also support guides, porters, lodges, and other local businesses, making Everest an important source of income alongside the pressures created by growing traffic.
As the highest mountain on Earth, Everest remains uniquely appealing to climbers. Three decades of data show just how much the human presence surrounding that pursuit has grown.
If you enjoyed today’s post, check out The Most Visited National Parks in the U.S. on Voronoi, the app from Visual Capitalist.
2026-10-04 02:27:12
This graphic, created by Julie R. Peasley, ranks cities among the 100 largest in the U.S. by 2024 population according to the Republican or Democratic presidential vote share in each city’s primary county.
Population data comes from the U.S. Census Bureau, while election results primarily come from the MIT Election Data and Science Lab.
The table below shows the 15 most Democratic major cities.
| Rank | City | Primary County | Democratic % | City Share of County Population |
|---|---|---|---|---|
| 1 | Washington, DC | District of Columbia | 90.3% | 100% |
| 2 | Baltimore, MD | Baltimore city | 84.6% | 100% |
| 3 | New Orleans, LA | Orleans Parish | 82.2% | 100% |
| 4 | Richmond, VA | Richmond city | 82.0% | 100% |
| 5 | St. Louis, MO | St. Louis city | 81.2% | 100% |
| 6 | San Francisco, CA | San Francisco County | 80.3% | 100% |
| 7 | Durham, NC | Durham County | 79.8% | 88% |
| 8 | Philadelphia, PA | Philadelphia County | 78.8% | 100% |
| 9 | Portland, OR | Multnomah County | 78.7% | 80% |
| 10 | Denver, CO | Denver County | 76.7% | 100% |
| 11 | Madison, WI | Dane County | 74.9% | 49% |
| 12 | Oakland, CA | Alameda County | 74.6% | 27% |
| 13 | Boston, MA | Suffolk County | 74.3% | 85% |
| 14 | Seattle, WA | King County | 73.6% | 33% |
| 15 | Atlanta, GA | Fulton County | 71.9% | 44% |
And here are the 15 most Republican major cities:
| Rank | City | Primary County | Republican % | City Share of County Population |
|---|---|---|---|---|
| 1 | Lubbock, TX | Lubbock County | 69.2% | 83% |
| 2 | Cape Coral, FL | Lee County | 63.9% | 27% |
| 3 | Bakersfield, CA | Kern County | 59.3% | 45% |
| 4 | Tulsa, OK | Tulsa County | 56.5% | 59% |
| 5 | Wichita, KS | Sedgwick County | 56.1% | 75% |
| 6 | Miami, FL | Miami-Dade County | 55.4% | 17% |
| 7 | Fort Wayne, IN | Allen County | 55.3% | 68% |
| 8 | Corpus Christi, TX | Nueces County | 55.2% | 90% |
| 9 | Frisco/McKinney/Plano, TX | Collin County | 54.2% | 52% |
| 10 | Port St. Lucie, FL | St. Lucie County | 54.2% | 66% |
| 11 | Boise, ID | Ada County | 53.8% | 44% |
| 12 | Colorado Springs, CO | El Paso County | 53.6% | 66% |
| 13 | Huntsville, AL | Madison County | 53.4% | 53% |
| 14 | St. Petersburg, FL | Pinellas County | 52.1% | 28% |
| 15 | Fort Worth/Arlington, TX | Tarrant County | 51.8% | 62% |
Washington, D.C. leads the blue side at 90.3%, followed by Baltimore at 84.6%. On the red side, Lubbock leads at 69.2%, followed by Cape Coral at 63.9% and Bakersfield at 59.3%.
One important caveat is that these are county-level election results, not city-level results. While Washington, Baltimore, Philadelphia, and Denver account for their entire county or county-equivalent, Oakland represents just 27% of Alameda County’s population and St. Petersburg 28% of Pinellas County.
The rankings show why broad state-level labels can obscure substantial local variation. California is a clear example: San Francisco and Oakland appear among the bluest major cities in the ranking, while Bakersfield lands on the red side, with Kern County voting 59.3% Republican.
Florida shows a different pattern. Cape Coral, Miami, Port St. Lucie, and St. Petersburg all appear among the 15 reddest major cities by this measure. Together, the results show how political geography can vary considerably within states and why county-level results can reveal patterns that statewide results do not.
Geography is only one way to examine America’s political divide. Age is another, with notable differences in political affiliation by generation in the U.S.
To explore another angle on the 2024 election, see How Americans Voted Based on Their View of the Economy on the Voronoi app.
2026-10-04 00:44:42
According to the IIE Open Doors 2025 report, 1.18 million international students studied at U.S. colleges and universities in 2024/25, up 5% year-over-year.
That was a record total, equivalent to roughly 6% of U.S. higher education enrollment. The longer-term rise has coincided with immigration becoming an increasingly important component of population growth across many U.S. states.
The following table shows international students by place of origin, based on data from the Institute of International Education.
| Country | Enrollment in 2023/24 | Enrollment in 2024/25 | % of Total (2024/25) | % Change |
|---|---|---|---|---|
India |
331,602 | 363,019 | 30.82 | 9.5 |
China |
277,398 | 265,919 | 22.58 | -4.1 |
South Korea |
43,149 | 42,293 | 3.59 | -2.0 |
Canada |
28,998 | 29,903 | 2.54 | 3.1 |
Vietnam |
22,066 | 25,584 | 2.17 | 15.9 |
Nepal |
16,742 | 24,890 | 2.11 | 48.7 |
Taiwan |
23,157 | 23,263 | 1.98 | 0.5 |
Nigeria |
20,029 | 21,847 | 1.86 | 9.1 |
Bangladesh |
17,099 | 20,156 | 1.71 | 17.9 |
Brazil |
16,877 | 17,277 | 1.47 | 2.4 |
Mexico |
15,474 | 15,652 | 1.33 | 1.2 |
Japan |
13,959 | 13,814 | 1.17 | -1.0 |
Pakistan |
10,988 | 13,165 | 1.12 | 19.8 |
Ghana |
9,394 | 12,825 | 1.09 | 36.5 |
Saudi Arabia |
14,828 | 12,702 | 1.08 | -14.3 |
Iran |
12,430 | 12,656 | 1.07 | 1.8 |
United Kingdom |
10,473 | 11,136 | 0.95 | 6.3 |
Colombia |
10,120 | 10,213 | 0.87 | 0.9 |
Turkey/Türkiye |
9,148 | 9,413 | 0.80 | 2.9 |
Spain |
8,842 | 9,229 | 0.78 | 4.4 |
Germany |
9,230 | 9,123 | 0.77 | -1.2 |
France |
8,543 | 8,698 | 0.74 | 1.8 |
Indonesia |
8,348 | 8,104 | 0.69 | -2.9 |
Italy |
6,545 | 6,744 | 0.57 | 3.0 |
Peru |
5,505 | 5,667 | 0.48 | 2.9 |
Hong Kong |
5,627 | 5,492 | 0.47 | -2.4 |
Kenya |
4,507 | 5,337 | 0.45 | 18.4 |
Thailand |
5,310 | 5,022 | 0.43 | -5.4 |
Kuwait |
5,102 | 5,018 | 0.43 | -1.6 |
Russia |
5,071 | 4,948 | 0.42 | -2.4 |
Australia |
4,432 | 4,620 | 0.39 | 4.2 |
Philippines |
4,100 | 4,573 | 0.39 | 11.5 |
Egypt |
4,280 | 4,518 | 0.38 | 5.6 |
Malaysia |
4,816 | 4,485 | 0.38 | -6.9 |
Singapore |
4,574 | 4,449 | 0.38 | -2.7 |
Venezuela |
3,904 | 3,886 | 0.33 | -0.5 |
Burma |
3,222 | 3,744 | 0.32 | 16.2 |
Sri Lanka |
3,424 | 3,661 | 0.31 | 6.9 |
Jamaica |
3,185 | 3,416 | 0.29 | 7.3 |
Ethiopia |
3,078 | 3,395 | 0.29 | 10.3 |
Argentina |
3,101 | 3,335 | 0.28 | 7.5 |
Ecuador |
3,256 | 3,282 | 0.28 | 0.8 |
Kazakhstan |
2,712 | 3,102 | 0.26 | 14.4 |
Chile |
3,113 | 3,092 | 0.26 | -0.7 |
South Africa |
2,814 | 2,952 | 0.25 | 4.9 |
Jordan |
2,643 | 2,768 | 0.24 | 4.7 |
Bahamas |
2,513 | 2,764 | 0.23 | 10.0 |
Zimbabwe |
1,907 | 2,712 | 0.23 | 42.2 |
Sweden |
2,572 | 2,665 | 0.23 | 3.6 |
Greece |
2,561 | 2,641 | 0.22 | 3.1 |
Honduras |
2,532 | 2,548 | 0.22 | 0.6 |
Netherlands |
2,546 | 2,462 | 0.21 | -3.3 |
Ukraine |
2,183 | 2,346 | 0.20 | 7.5 |
Israel |
2,167 | 2,266 | 0.19 | 4.6 |
Panama |
2,128 | 2,233 | 0.19 | 4.9 |
Mongolia |
1,671 | 1,991 | 0.17 | 19.2 |
Morocco |
1,784 | 1,975 | 0.17 | 10.7 |
Lebanon |
1,987 | 1,826 | 0.16 | -8.1 |
Poland |
1,661 | 1,809 | 0.15 | 8.9 |
United Arab Emirates |
1,571 | 1,808 | 0.15 | 15.1 |
Congo, Dem. Rep. of the (Kinshasa) |
1,738 | 1,794 | 0.15 | 3.2 |
New Zealand |
1,696 | 1,781 | 0.15 | 5.0 |
Norway |
1,692 | 1,617 | 0.14 | -4.4 |
Dominican Republic |
1,542 | 1,582 | 0.13 | 2.6 |
Uganda |
1,303 | 1,495 | 0.13 | 14.7 |
Bolivia |
1,357 | 1,463 | 0.12 | 7.8 |
Costa Rica |
1,431 | 1,461 | 0.12 | 2.1 |
Trinidad and Tobago |
1,334 | 1,419 | 0.12 | 6.4 |
Ireland |
1,423 | 1,404 | 0.12 | -1.3 |
Oman |
1,748 | 1,401 | 0.12 | -19.9 |
Kyrgyzstan |
977 | 1,386 | 0.12 | 41.9 |
El Salvador |
1,451 | 1,384 | 0.12 | -4.6 |
Switzerland |
1,383 | 1,382 | 0.12 | -0.1 |
Rwanda |
1,311 | 1,359 | 0.12 | 3.7 |
Guatemala |
1,352 | 1,344 | 0.11 | -0.6 |
Azerbaijan |
1,130 | 1,329 | 0.11 | 17.6 |
Uzbekistan |
1,219 | 1,310 | 0.11 | 7.5 |
Cambodia |
997 | 1,201 | 0.10 | 20.5 |
Côte d’Ivoire |
1,138 | 1,188 | 0.10 | 4.4 |
Albania |
1,187 | 1,184 | 0.10 | -0.3 |
Cameroon |
981 | 1,181 | 0.10 | 20.4 |
Denmark |
1,329 | 1,172 | 0.10 | -11.8 |
Tanzania |
1,027 | 1,140 | 0.10 | 11.0 |
Portugal |
1,111 | 1,137 | 0.10 | 2.3 |
Belgium |
1,037 | 1,059 | 0.09 | 2.1 |
Austria |
1,017 | 1,043 | 0.09 | 2.6 |
Georgia |
991 | 1,040 | 0.09 | 4.9 |
Romania |
902 | 956 | 0.08 | 6.0 |
Serbia |
894 | 940 | 0.08 | 5.1 |
Haiti |
883 | 896 | 0.08 | 1.5 |
Hungary |
758 | 848 | 0.07 | 11.9 |
Czech Republic |
803 | 840 | 0.07 | 4.6 |
Tunisia |
717 | 769 | 0.07 | 7.3 |
Zambia |
597 | 743 | 0.06 | 24.5 |
Afghanistan |
702 | 712 | 0.06 | 1.4 |
Nicaragua |
618 | 696 | 0.06 | 12.6 |
Paraguay |
642 | 665 | 0.06 | 3.6 |
Bulgaria |
576 | 612 | 0.05 | 6.3 |
Malawi |
502 | 610 | 0.05 | 21.5 |
Iraq |
476 | 572 | 0.05 | 20.2 |
Finland |
482 | 543 | 0.05 | 12.7 |
Armenia |
497 | 525 | 0.04 | 5.6 |
Bosnia and Herzegovina |
247 | 517 | 0.04 | 109.3 |
Palestinian Territories |
466 | 500 | 0.04 | 7.3 |
Senegal |
508 | 498 | 0.04 | -2.0 |
Angola |
511 | 478 | 0.04 | -6.5 |
Sierra Leone |
385 | 462 | 0.04 | 20.0 |
Uruguay |
420 | 451 | 0.04 | 7.4 |
Turkmenistan |
380 | 447 | 0.04 | 17.6 |
Cyprus |
409 | 438 | 0.04 | 7.1 |
Bahrain |
335 | 438 | 0.04 | 30.7 |
Syria |
385 | 434 | 0.04 | 12.7 |
Gambia, The |
363 | 430 | 0.04 | 18.5 |
Algeria |
364 | 426 | 0.04 | 17.0 |
Sudan |
398 | 417 | 0.04 | 4.8 |
Dominica |
406 | 414 | 0.04 | 2.0 |
Belarus |
389 | 411 | 0.03 | 5.7 |
Macau |
408 | 397 | 0.03 | -2.7 |
Belize |
416 | 382 | 0.03 | -8.2 |
Croatia |
390 | 369 | 0.03 | -5.4 |
Slovakia |
326 | 366 | 0.03 | 12.3 |
Qatar |
388 | 350 | 0.03 | -9.8 |
Guyana |
365 | 344 | 0.03 | -5.8 |
Lithuania |
322 | 343 | 0.03 | 6.5 |
Libya |
365 | 333 | 0.03 | -8.8 |
Iceland |
328 | 320 | 0.03 | -2.4 |
Burkina Faso |
299 | 309 | 0.03 | 3.3 |
Botswana |
273 | 303 | 0.03 | 11.0 |
Barbados |
282 | 296 | 0.03 | 5.0 |
Liberia |
261 | 290 | 0.02 | 11.1 |
Latvia |
262 | 271 | 0.02 | 3.4 |
Benin |
260 | 267 | 0.02 | 2.7 |
Yemen |
256 | 258 | 0.02 | 0.8 |
Madagascar |
240 | 251 | 0.02 | 4.6 |
Mali |
239 | 249 | 0.02 | 4.2 |
Togo |
240 | 247 | 0.02 | 2.9 |
Mauritius |
258 | 239 | 0.02 | -7.4 |
Slovenia |
199 | 236 | 0.02 | 18.6 |
Gabon |
250 | 235 | 0.02 | -6.0 |
Tajikistan |
198 | 234 | 0.02 | 18.2 |
Bhutan |
184 | 228 | 0.02 | 23.9 |
Bermuda |
237 | 228 | 0.02 | -3.8 |
Burundi |
199 | 220 | 0.02 | 10.6 |
Eswatini |
210 | 219 | 0.02 | 4.3 |
Niger |
171 | 219 | 0.02 | 28.1 |
Equatorial Guinea |
234 | 217 | 0.02 | -7.3 |
Saint Lucia |
197 | 216 | 0.02 | 9.6 |
Estonia |
195 | 208 | 0.02 | 6.7 |
Saint Kitts and Nevis |
193 | 208 | 0.02 | 7.8 |
North Macedonia |
206 | 205 | 0.02 | -0.5 |
Grenada |
160 | 200 | 0.02 | 25.0 |
Mozambique |
175 | 198 | 0.02 | 13.1 |
Tonga |
185 | 195 | 0.02 | 5.4 |
Kosovo |
189 | 190 | 0.02 | 0.5 |
Antigua and Barbuda |
183 | 186 | 0.02 | 1.6 |
Congo, Republic of the (Brazzaville) |
180 | 178 | 0.02 | -1.1 |
Montenegro |
148 | 169 | 0.01 | 14.2 |
Fiji |
156 | 165 | 0.01 | 5.8 |
Cayman Islands |
157 | 164 | 0.01 | 4.5 |
Moldova |
154 | 154 | 0.01 | 0.0 |
South Sudan |
96 | 137 | 0.01 | 42.7 |
Luxembourg |
108 | 133 | 0.01 | 23.1 |
Somalia |
117 | 128 | 0.01 | 9.4 |
Laos |
114 | 124 | 0.01 | 8.8 |
Papua New Guinea |
109 | 118 | 0.01 | 8.3 |
Chad |
66 | 115 | 0.01 | 74.2 |
Saint Vincent and the Grenadines |
104 | 112 | 0.01 | 7.7 |
Malta |
72 | 97 | 0.01 | 34.7 |
Namibia |
82 | 95 | 0.01 | 15.9 |
Cuba |
117 | 91 | 0.01 | -22.2 |
Guinea |
78 | 83 | 0.01 | 6.4 |
Sint Maarten |
72 | 81 | 0.01 | 12.5 |
Eritrea |
73 | 80 | 0.01 | 9.6 |
Samoa |
76 | 75 | 0.01 | -1.3 |
Lesotho |
75 | 70 | 0.01 | -6.7 |
Aruba |
58 | 69 | 0.01 | 19.0 |
French Polynesia |
60 | 66 | 0.01 | 10.0 |
British Virgin Islands |
45 | 61 | 0.01 | 35.6 |
Palau |
33 | 58 | 0.005 | 75.8 |
Cabo Verde |
51 | 57 | 0.005 | 11.8 |
Kiribati |
61 | 56 | 0.005 | -8.2 |
Micronesia, Federated States of |
28 | 52 | 0.004 | 85.7 |
Timor-Leste |
29 | 47 | 0.004 | 62.1 |
Suriname |
46 | 45 | 0.004 | -2.2 |
Maldives |
33 | 42 | 0.004 | 27.3 |
Turks and Caicos |
40 | 40 | 0.003 | 0.0 |
Mauritania |
38 | 37 | 0.003 | -2.6 |
Curacao |
50 | 37 | 0.003 | -26.0 |
Monaco |
17 | 32 | 0.003 | 88.2 |
Brunei |
33 | 31 | 0.003 | -6.1 |
Marshall Islands, Republic of the |
10 | 30 | 0.003 | 200.0 |
Andorra |
22 | 28 | 0.002 | 27.3 |
Comoros |
56 | 22 | 0.002 | -60.7 |
Cook Islands |
11 | 18 | 0.002 | 63.6 |
Vanuatu |
12 | 18 | 0.002 | 50.0 |
Liechtenstein |
16 | 17 | 0.001 | 6.3 |
Seychelles |
17 | 16 | 0.001 | -5.9 |
Djibouti |
9 | 13 | 0.001 | 44.4 |
Anguilla |
8 | 12 | 0.001 | 50.0 |
Stateless |
13 | 12 | 0.001 | -7.7 |
Central African Republic |
20 | 11 | 0.001 | -45.0 |
Guinea-Bissau |
11 | 9 | 0.001 | -18.2 |
Martinique |
7 | 8 | 0.001 | 14.3 |
Solomon Islands |
5 | 8 | 0.001 | 60.0 |
Gibraltar |
12 | 7 | 0.001 | -41.7 |
Reunion |
8 | 6 | 0.001 | -25.0 |
Guadeloupe |
4 | 6 | 0.001 | 50.0 |
French Guiana |
1 | 4 | 0.0003 | 300.0 |
Niue |
1 | 4 | 0.0003 | 300.0 |
San Marino |
2 | 3 | 0.0003 | 50.0 |
Tuvalu |
2 | 3 | 0.0003 | 50.0 |
Europe, Unspecified |
0 | 2 | 0.0002 | — |
Montserrat |
3 | 2 | 0.0002 | -33.3 |
New Caledonia |
1 | 2 | 0.0002 | 100.0 |
São Tomé and Príncipe |
0 | 1 | 0.0001 | — |
Saint Helena |
3 | 1 | 0.0001 | -66.7 |
Wallis and Futuna |
0 | 1 | 0.0001 | — |
Falkland Islands/Islas Malvinas |
2 | 0 | 0.0000 | -100.0 |
World Total |
1,126,690 | 1,177,766 | 100 | — |
India widened its lead as the largest source of international students in the U.S. Its student population rose 9.5% to 363,019, while China’s fell 4.1% to 265,919.
Nepal (+48.7%), Ghana (+36.5%), and Pakistan (+19.8%) were among the fastest-growing major sources.
Despite the record number of international students in 2024/25, signs of slower growth were already emerging. The overall total was partly supported by Optional Practical Training (OPT), which allows eligible graduates to work temporarily in their field of study. OPT participation jumped 21% to 294,253, while new international enrollment fell 7%.
Indian and Chinese students, among other nationalities, value the U.S. OPT program because it allows eligible graduates to gain work experience after graduation and can provide a pathway toward H-1B sponsorship.
That divergence became more pronounced in fall 2025. IIE’s snapshot of 828 U.S. institutions found that new international enrollment fell 17% from the previous year. Graduate enrollment declined 12%, while undergraduate enrollment rose 2% and OPT participation increased 14%.
Visa rules are only part of the picture. A 2024 survey cited by the Migration Policy Institute found that 60% of 1,252 Chinese graduate students surveyed reported discrimination on campus. The study focused mainly on students in STEM fields, while many respondents also cited educational quality and life experience as reasons for choosing the United States.
Policy uncertainty has also increased. Recent changes and proposals have included tighter visa screening and restrictions affecting international students, although some measures have faced legal challenges. Along with growing competition from universities abroad, these factors could influence where future international students choose to study.
For another look at American higher education, see Ranked: Median Student Debt for a U.S. College Degree on the Voronoi app.