Mapped: The World’s Fastest (and Slowest) Internet Speeds
How quickly did this page load for you?
The answer depends on the device you’re using, and where in the world you’re located. Average internet speeds vary wildly from country to country.
Which countries have the fastest internet connection? Using data from the Cable.co.uk, this map ranks the fastest (and slowest) internet speeds worldwide by comparing the fixed broadband speeds of over 200 countries.
What Factors Affect Internet Speed?
Before diving in, it’s important to understand the key factors that impact a country’s internet speed. Generally speaking, internet speed depends on:
- Infrastructure or the type of cabling (copper or fiber-optic) that a country’s utilizing to support their internet service. Typically, the newer the infrastructure, the faster the connection.
- Proximity/connection to submarine cables is important, as these massive undersea fiber-optic cables transmit about 97% of the world’s communication data.
- The size of a country, since landmass affects how much it costs to upgrade infrastructure. The smaller the country, the cheaper it is to upgrade cabling.
- Investment makes a difference, or how much a country’s government prioritizes internet accessibility.
Of course, other factors may influence a country’s internet speed too, such as government regulation and intentional bandwidth throttling, which is the case in countries like Turkmenistan.
Ranked: Fixed Broadband Speeds
To measure fixed broadband speeds across the globe, Cable.co.uk used more than 1.1 billion speed tests, sourced from over 200 countries.
The region with the fastest connection is Jersey, which is one of the islands that make up the British Isles. It has an average download speed of 274.27 mbps—almost 9x the overall average.
|Rank||Country||Mean download speed (Mbps)|
|7||🇲🇴 Macao SAR||128.56|
|14||🇺🇸 United States||92.42|
|15||🇭🇰 Hong Kong SAR||91.04|
|20||🇳🇿 New Zealand||85.95|
|23||🇦🇽 Aland Islands||81.31|
|26||🇻🇦 Vatican City||73.49|
|27||🇰🇾 Cayman Islands||71.47|
|35||🇰🇷 Republic of Korea||61.72|
|37||🇱🇹 Republic of Lithuania||56.17|
|40||🇸🇰 Slovak Republic||54.92|
|42||🇮🇲 Isle of Man||52.1|
|43||🇬🇧 United Kingdom||51.48|
|48||🇵🇲 Saint Pierre and Miquelon||47.92|
|53||🇸🇲 San Marino||40.55|
|54||🇵🇷 Puerto Rico||40.52|
|56||🇲🇫 Saint Martin||40.19|
|63||🇲🇩 Republic of Moldova||36.47|
|64||🇹🇨 Turks and Caicos Islands||36.09|
|65||🇹🇹 Trinidad and Tobago||35.81|
|66||🇷🇺 Russian Federation||35.73|
|69||🇳🇨 New Caledonia||31.79|
|70||🇧🇦 Bosnia and Herzegovina||31.72|
|73||🇦🇪 United Arab Emirates||29.9|
|75||🇻🇮 Virgin Islands, U.S.||29.34|
|83||🇫🇴 Faroe Islands||21.59|
|90||🇿🇦 South Africa||19.94|
|93||🇧🇶 Bonaire, Saint Eustatius and Saba||19.6|
|95||🇻🇬 Virgin Islands, British||19.4|
|97||🇨🇷 Costa Rica||19.02|
|99||🇸🇦 Saudi Arabia||18.1|
|107||🇲🇰 North Macedonia||15.38|
|108||🇯🇴 Hashemite Kingdom of Jordan||15.25|
|109||🇱🇨 Saint Lucia||15.02|
|111||🇻🇨 Saint Vincent and the Grenadines||14.32|
|114||🇲🇵 Northern Mariana Islands||13.15|
|116||🇰🇳 Saint Kitts and Nevis||12.96|
|118||🇧🇱 Saint Barthélemy||12.25|
|120||🇨🇬 Republic of the Congo||12.07|
|122||🇩🇴 Dominican Republic||11.87|
|123||🇦🇸 American Samoa||11.76|
|127||🇬🇫 French Guiana||10.99|
|128||🇧🇫 Burkina Faso||10.73|
|131||🇸🇻 El Salvador||9.95|
|132||🇱🇰 Sri Lanka||9.95|
|136||🇨🇮 Cote D'Ivoire||9.54|
|141||🇦🇬 Antigua and Barbuda||8.69|
|144||🇹🇿 United Republic of Tanzania||8.6|
|149||🇨🇻 Cape Verde||7.94|
|152||🇵🇫 French Polynesia||7.67|
|165||🇲🇭 Marshall Islands||6.71|
|170||🇸🇽 Sint Maarten||6.15|
|171||🇱🇦 Lao People's Democratic Republic||5.91|
|177||🇸🇧 Solomon Islands||5.33|
|179||🇵🇬 Papua New Guinea||5.1|
|191||🇨🇩 DR Congo||3.63|
|204||🇸🇹 São Tomé and Príncipe||2.43|
|208||🇸🇱 Sierra Leone||2.19|
|213||🇸🇾 Syrian Arab Republic||1.67|
|214||🇫🇲 Federated States of Micronesia||1.63|
|218||🇸🇸 South Sudan||1.4|
|219||🇹🇱 Democratic Republic of Timor-Leste||1.33|
|220||🇬🇶 Equatorial Guinea||1.3|
Infrastructure is a major reason behind Jersey’s speedy internet. It’s the first jurisdiction in the world to upgrade its entire system to pure fibre (FTTP). But the region’s size also plays a factor, since its landmass and population size are both relatively small compared to the rest of the world.
Second on the list is another small region, Liechtenstein, with an average download speed of 211.26 mbps. Liechtenstein is one of the richest countries in the world per capita, and its government has invested heavily in its telecommunications infrastructure, aiming to be fully fibre optic by 2022.
Like Jersey, Liechtenstein also has a relatively small population. At the time of this article’s publication, the region is home to approximately 38,000 people. In fact, it’s worth noting that of the top ten regions, only two have populations over one million—the Netherlands, and Hungary.
At the opposite end of the spectrum, Turkmenistan has the slowest fixed broadband, with a speed of 0.5 mbps. As mentioned above, this is largely because of government regulation and intervention.
The Future is 5G
Innovation and new technologies are changing the digital landscape, and things like 5G networks are becoming more mainstream across the globe.
Because of the rapidly changing nature of this industry, the data behind this ranking is updated monthly to provide the latest look at internet speeds across the globe.
This means the bar is gradually raising when it comes to internet speed, as faster, stronger internet connections become the norm. And countries that aren’t equipped to handle these souped-up networks will lag behind even further.
Charted: The Exponential Growth in AI Computation
In eight decades, artificial intelligence has moved from purview of science fiction to reality. Here’s a quick history of AI computation.
Charted: The Exponential Growth in AI Computation
Electronic computers had barely been around for a decade in the 1940s, before experiments with AI began. Now we have AI models that can write poetry and generate images from textual prompts. But what’s led to such exponential growth in such a short time?
The Three Eras of AI Computation
In the 1950s, American mathematician Claude Shannon trained a robotic mouse called Theseus to navigate a maze and remember its course—the first apparent artificial learning of any kind.
Theseus was built on 40 floating point operations (FLOPs), a unit of measurement used to count the number of basic arithmetic operations (addition, subtraction, multiplication, or division) that a computer or processor can perform in one second.
Computation power, availability of training data, and algorithms are the three main ingredients to AI progress. And for the first few decades of AI advances, compute, which is the computational power needed to train an AI model, grew according to Moore’s Law.
|1950–2010||Pre-Deep Learning||18–24 months|
|2010–2016||Deep Learning||5–7 months|
|2016–2022||Large-scale models||11 months|
Source: “Compute Trends Across Three Eras of Machine Learning” by Sevilla et. al, 2022.
However, at the start of the Deep Learning Era, heralded by AlexNet (an image recognition AI) in 2012, that doubling timeframe shortened considerably to six months, as researchers invested more in computation and processors.
With the emergence of AlphaGo in 2015—a computer program that beat a human professional Go player—researchers have identified a third era: that of the large-scale AI models whose computation needs dwarf all previous AI systems.
Predicting AI Computation Progress
Looking back at the only the last decade itself, compute has grown so tremendously it’s difficult to comprehend.
For example, the compute used to train Minerva, an AI which can solve complex math problems, is nearly 6 million times that which was used to train AlexNet 10 years ago.
Here’s a list of important AI models through history and the amount of compute used to train them.
|Perceptron Mark I||1957–58||695,000|
|AlphaGo||2016||1.9 million petaFLOPs|
|GPT-3||2020||314 million petaFLOPs|
|Minerva||2022||2.7 billion petaFLOPs|
Note: One petaFLOP = one quadrillion FLOPs. Source: “Compute Trends Across Three Eras of Machine Learning” by Sevilla et. al, 2022.
The result of this growth in computation, along with the availability of massive data sets and better algorithms, has yielded a lot of AI progress in seemingly very little time. Now AI doesn’t just match, but also beats human performance in many areas.
It’s difficult to say if the same pace of computation growth will be maintained. Large-scale models require increasingly more compute power to train, and if computation doesn’t continue to ramp up it could slow down progress. Exhausting all the data currently available for training AI models could also impede the development and implementation of new models.
However with all the funding poured into AI recently, perhaps more breakthroughs are around the corner—like matching the computation power of the human brain.
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