| April 17, 2023

47 New Ookla Market Reports Available for Q1 2023

Ookla® Market Reports™ identify key data about internet performance in countries across the world. This quarter we’ve provided updated analyses for 47 markets using Speedtest Intelligence® and summarized a few top takeaways below. Click through to the market report to see more details and charts about the countries you’re interested in, including the fastest fixed broadband providers and mobile operators, who had the most consistent service, and 5G and device performance in select countries during Q1 2023. Jump forward to a continent using these links:

Africa | Americas | Asia | Europe | Oceania

Africa

  • Cameroon: Speedtest Intelligence reveals that MTN had the fastest median mobile download speed in Cameroon at 14.46 Mbps during Q1 2023. blue had the lowest median mobile multi-server latency at 184 ms.
  • Ethiopia: Safaricom had the fastest median mobile download speed at 32.81 Mbps during Q1 2023. Ethio Telecom had the lowest median mobile multi-server latency at 55 ms.
  • Tanzania: There were no winners over fastest fixed broadband and mobile in Tanzania during Q1 2023. Dar es Salaam had the fastest median mobile download speed among Tanzania’s most populous cities at 28.73 Mbps during Q1 2023.

Americas

  • Argentina: Personal had the fastest median download speed over mobile (32.62 Mbps) and Movistar was fastest for fixed broadband (94.26 Mbps). Movistar had the lowest median multi-server latency over fixed broadband at 12 ms.
  • Belize: NEXGEN had the fastest median download over fixed broadband in Belize at 47.35 Mbps. Digi had the fastest median mobile download speed at 18.39 Mbps.
  • Canada: Bell was the fastest mobile operator in Canada with a median download speed of 111.11 Mbps at Q1 2023. Bell also had the fastest median 5G download speed at 183.29 Mbps. Bell pure fibre was fastest for fixed broadband (281.94 Mbps). 
  • Colombia: Movistar was fastest for fixed broadband with a median download speed of 151.74 Mbps. ETB had the lowest median multi-server latency over fixed broadband at 8 ms.
  • Dominican Republic: Claro had the fastest median download speed among mobile operators at 32.01 Mbps. Viva had the lowest mobile multi-server latency at 43 ms. SpaceX’s Starlink was fastest for fixed broadband at 45.65 Mbps. 
  • Ecuador: The fastest mobile operator was CNT with a median download speed of 30.82 Mbps. Netlife was fastest for fixed broadband (71.82 Mbps). Fibramax had the lowest multi-server latency over fixed broadband at 9 ms. 
  • El Salvador: Claro had the fastest median download speed over mobile in El Salvador at 39.09 Mbps.
  • Guatemala: Claro was the fastest mobile operator in Guatemala with a median download speed of 33.13 Mbps. Claro also had the highest Consistency with 84.5% of results showing at least a 5 Mbps minimum download speed and 1 Mbps minimum upload speed.
  • Guyana: ENet was the fastest fixed broadband provider (60.27 Mbps), while Digicel was the fastest mobile operator (35.60 Mbps). ENet also had the lowest median multi-server latency over fixed broadband at 120 ms.
  • Haiti: Digicel was the fastest mobile operator in Haiti with a median mobile download speed of 11.12 Mbps. SpaceX Starlink had the fastest fixed broadband internet at 46.76 Mbps. Natcom had the lowest median mobile multi-server latency at 62 ms. 
  • Jamaica: Flow was the fastest fixed broadband provider in Jamaica with a median download speed of 50.50 Mbps. Flow also had the lowest median multi-server latency at 36 ms.
  • Mexico: Telcel had the fastest median download speed over mobile at 45.54 Mbps. Totalplay was fastest for fixed broadband (78.94 Mbps) and had the lowest median multi-server latency at 26 ms.
  • Peru: Claro was the fastest mobile operator with a median download speed of 22.39 Mbps. Apple devices had the fastest median download speed among top device manufacturers at 29.68 Mbps.
  • Suriname: Telesur had the fastest median download speed over mobile at 51.18 Mbps. There was no winner over fixed broadband, but Digicel+ had the lowest median multi-server latency at 57 ms.
  • Trinidad and Tobago: Digicel had the fastest median download speed over mobile at 37.56 Mbps. Digicel+ had the fastest median fixed broadband download speed at 94.27 Mbps and the lowest median multi-server latency at 7 ms.
  • United States: T-Mobile was the fastest mobile operator with a median download speed of 165.22 Mbps. T-Mobile also had the fastest median 5G download speed at 220.70 Mbps. Spectrum edged out XFINITY as the fastest fixed broadband provider with a median download speed of 234.80 Mbps. Verizon had the lowest median multi-server latency on fixed broadband at 15 ms.

Asia

  • Afghanistan: The fastest mobile operator in Afghanistan was Afghan Wireless (5.92 Mbps), which also had the lowest median multi-server latency at 84 ms.
  • Bangladesh: Banglalink was the fastest mobile operator in Bangladesh with a median download speed of 21.94 Mbps. DOT Internet was fastest over fixed broadband at 89.50 Mbps and had the lowest median multi-server latency at 5 ms.
  • Bhutan: There was no fastest mobile operator in Bhutan during Q1 2023, but BT had the lowest median multi-server latency at 66 ms.
  • Brunei: There was no statistical winner on mobile during Q1 2023, but Apple devices had the fastest median download speed at 113.48 Mbps.
  • Cambodia: SINET had the fastest median download speed over fixed broadband (42.00 Mbps). Cellcard was fastest over mobile at 32.05 Mbps.
  • China: China Mobile was the fastest mobile operator with a median download speed of 138.95 Mbps. China Mobile also had the fastest median mobile 5G download speed at 291.24 Mbps. China Unicom was fastest for fixed broadband at 221.07 Mbps.
  • Georgia: MagtiCom had the fastest median fixed broadband speed in Georgia at 27.65 Mbps during Q1 2023. MagtiCom also had the lowest median multi-server latency at 11 ms. Geocell was fastest over mobile at 40.81 Mbps.
  • Indonesia: Telkomsel was the fastest Indonesian mobile operator with a median download speed of 24.48 Mbps. Telkomsel also had the lowest median mobile multi-server latency at 45 ms.
  • Japan: NTT DoCoMo was the fastest mobile operator with a median download speed of 48.86 Mbps during Q1 2023. So-net had the fastest fixed broadband speed at 282.13 Mbps, as well as the lowest median multi-server latency at 9 ms.
  • Malaysia: TIME was the fastest fixed broadband provider in Malaysia (107.56 Mbps) and had the lowest multi-server latency at 9 ms.
  • Pakistan: Transworld had the fastest median fixed broadband download speed in Pakistan at 16.23 Mbps. Jazz was fastest over mobile at 21.93 Mbps. Zong had the lowest median mobile multi-server latency at 46 ms.
  • Philippines: Smart delivered the fastest mobile download speed in the Philippines (33.39 Mbps). 
  • Singapore: Singtel had the fastest median download speed over mobile at 119.66 Mbps. StarHub had the lowest median mobile multi-server latency at 26 ms. SingTel had the fastest fixed broadband speed (263.13 Mbps). 
  • South Korea: KT delivered the fastest median download speed over fixed broadband in South Korea at 145.28 Mbps. SK Telecom had the fastest mobile speed at 194.41 Mbps.
  • Sri Lanka: SLT-Mobitel delivered the fastest mobile and fixed broadband speeds in Sri Lanka at 20.62 Mbps and 44.76 Mbps, respectively. Dialog had the lowest median mobile multi-server latency at 36 ms.
  • United Arab Emirates: Etisalat had the fastest median fixed download speed (255.01 Mbps) and median mobile download speed (184.58 Mbps) in the UAE during Q1 2023. Etisalat also had the fastest median 5G download speed at 672.04 Mbps and lowest median multi-server latency at 35 ms.

Europe

  • Albania: ONE overtook Vodafone as the fastest mobile operator in Albania with a median download speed of 48.44 Mbps during Q1 2023. ONE also had the lowest median mobile multi-server latency at 34 ms. Digicom was fastest for fixed broadband (87.71 Mbps).
  • Belgium: Telenet had the fastest median download speed over fixed broadband at 135.65 Mbps, while Telenet/BASE had the fastest median download speed over mobile at 69.48 Mbps.
  • Denmark: YouSee was the fastest mobile operator in Denmark with a median download speed of 137.28 Mbps. Hiper was fastest for fixed broadband at 258.41 Mbps.
  • Estonia: The fastest mobile operator in Estonia was Telia with a median download speed of 91.34 Mbps. Telia had the lowest median multi-server latency on mobile at 30 ms. Elisa was fastest over fixed broadband at 92.20 Mbps. 
  • Finland: DNA had the fastest median download speed over mobile at 101.59 Mbps. Lounea was fastest for fixed broadband at 107.84 Mbps and had the lowest median multi-server latency at 11 ms.
  • Germany: Telekom was the fastest mobile operator in Germany with a median download speed of 96.61 Mbps. Deutsche Glasfaser overtook Vodafone as the fastest fixed broadband provider at 183.20 Mbps. Deutsche Glasfaser also had the lowest median multi-server latency at 14 ms.
  • Latvia: While there was no fastest mobile operator in Latvia during Q1 2023, Balticom was fastest for fixed broadband with a median download speed of 238.41 Mbps. Balticom also had the lowest median fixed broadband multi-server latency at 4 ms.
  • Lithuania: The mobile operator with the fastest median download speed was Telia at 109.53 Mbps. Cgates was fastest for fixed broadband at 151.33 Mbps.
  • Poland: UPC was the fastest provider for fixed broadband with a median download speed of 214.34 Mbps. There was no statistical winner over mobile during Q1 2023.
  • Switzerland: Salt blazed ahead for the fastest fixed broadband with a median download speed of 367.36 Mbps. Salt also had the lowest median multi-server latency over fixed broadband at 8 ms.
  • Turkey: Turkcell was the fastest mobile operator in Turkey with a median download speed of 51.76 Mbps. Türk Telekom had the lowest median mobile multi-server latency at 38 ms. TurkNet was fastest for fixed broadband at 58.85 Mbps. 

Oceania

  • New Zealand: MyRepublic had the fastest median download speed over fixed broadband in New Zealand at 287.90 Mbps. There were no statistical winners among top mobile operators.

The Speedtest Global Index is your resource to understand how internet connectivity compares around the world and how it’s changing. Check back next month for updated data on country and city rankings, and look for updated Ookla Market Reports with Q2 2023 data in July.

Editor’s note: This article was updated on April 18 to exclude data from Vietnam while we continue to investigate anomalies in the market.

Ookla retains ownership of this article including all of the intellectual property rights, data, content graphs and analysis. This article may not be quoted, reproduced, distributed or published for any commercial purpose without prior consent. Members of the press and others using the findings in this article for non-commercial purposes are welcome to publicly share and link to report information with attribution to Ookla.

| November 5, 2020

Unable to Connect — The Most Significant Online Service Outages in Q3 2020

“Is it down?” frustrated users asked themselves during the multiple online service outages in Q3 2020. The fourth installment of our online service outage tracking series used Downdetector® data from Q3 2020 and focused on the following online service categories: cloud services, collaboration platforms, financial services, gaming, internet service providers and social media.

Cloud services

Cloudflare (July 17, 2020): 14,198 reports at peak

Downdetector_Cloudflare_Outage_1020

On July 17, a major disruption in Cloudflare’s service broke the internet, taking multiple online services down with it. Users rushed to Downdetector to log issues with multiple services that rely on Cloudflare for content delivery, including 4chan, DoorDash and Zendesk. At the peak of the outage, there were 14,198 reports of issues with the service in the U.S.

Azure (September 28, 2020): 2,846 reports at peak

Azure, Microsoft’s cloud service, was affected by September 28’s Microsoft-wide outage (see next category). Users from Germany, India, Japan and the U.S. stated they had issues with the cloud service. That day, there were 2,846 reports of issues at the peak of the outage in the U.S.

Collaboration platforms

Office 365 (September 28,2020): 20,437 reports at peak

Downdetector_Office365_Outage_1020

Microsoft’s suite of online collaboration services including Outlook, Sharepoint, OneDrive and Skype went down on September 28 (along with Azure, see above). Logs of issues with the services started coming into Downdetector at 3 p.m Pacific. Most users stated being unable to log in or connect to the server. At the peak, there were 20,437 reported issues in the U.S. Users from Japan and India also logged problems with the service that day.

Zoom (August 24, 2020): 17,874 reports at peak

On August 24, users were upset to find that they were unable to connect with their coworkers, friends and family through Zoom. Most users stated problems with logging in and joining a conference. There were 17,874 reports of issues in the U.S. at the peak of the outage. Users in the U.K. and Canada also had issues with the video conferencing service that day.

Google Drive (September 24, 2020): 14,715 reports at peak

Users in the U.S., Philippines and Indonesia were unable to collaborate on projects, upload files or access their documents stored in Google Drive on September 24. At the peak of the outage in the U.S., there were 14,715 reported issues. Users of Google products YouTube and Gmail also logged issues in Brazil, Germany, India, Japan, Mexico and the U.K.

Slack (September 29, 2020): 1,396 reports at peak

Slack received 1,396 logs of issues at the peak of the outage reports on September 29. Users in the U.S. had problems with sending messages, videos and images to their peers — and some were unable to connect to the platform at all.

Financial services

TD Ameritrade (August 18, 2020): 7,814 reports at peak

Downdetector_TD-Ameritrade_Outage_1020

The online stock investment tool reportedly went down on August 18. Users were unable to log into their account or buy and sell stocks. At the peak of the outage, there were 7,814 reports of issues in the U.S. There were two other notable outages that month — August 17 with 5,816 reports at peak and August 31 with 6,893 reports at peak.

Gaming

Steam (August 5, 2020): 69,255 reports at peak

Downdetector_Steam_Outage_1020

Users from Brazil, Germany, Japan, the U.K and the U.S. submitted issues with Steam on August 5. Most users stated problems when trying to log into the platform and play with other users. At the peak of the outage in the U.S, there were 69,255 reports of issues with the gaming platform.

Fall Guys (September 2, 2020): 2,890 reports at peak

The Fall Guys status page on Downdetector showed there were problems with the popular online game on September 2. Users in Brazil, the U.K. and the U.S. were struggling to play the game online. That day, 97% of reports stated problems with the server connection.

Internet service providers

Spectrum (July 29, 2020): 56,318 reports at peak

Downdetector_Spectrum_Outage_1020

Spectrum users from the both coasts of the United States flooded Downdetector with logs of issues with the service when they started experiencing problems with their internet connections. Complaints with the service started surging at around 5 p.m. Pacific and lasted for about an hour. At the peak of the outage there were 56,318 reports of issues.

CenturyLink (August 30, 2020): 11,543 reports at peak

CenturyLink customers on the East Coast of the U.S. had problems with their internet service on August 30 starting around 2 a.m. Pacific and ending around 8 a.m. Pacific. There were 11,543 reports of issues at the peak of the outage.

Social Media

WhatsApp (July 14, 2020): 148,573 reports at peak

Downdetector_WhatsApp_Outage_1020-1

A multi-country outage affected WhatsApp on July 14. Users from all over the world stated problems with sending and receiving messages on the Facebook-owned app. The country with the most issues submitted was Germany with 148,573 reports of issues at the peak of the outage. Users in Brazil, India, the Netherlands, Mexico, Spain and the U.K. were also affected by the outage.

Facebook (September 17, 2020): 30,918 reports at peak

Facebook users from multiple countries experienced problems with the social media platform on September 17. More than half of the logs were labeled as “total blackout” — users were unable to access the platform or any of its features. There were 30,918 reports of issues at the peak of the outage in the U.S. Users in Italy, Poland and the U.K. also had problems with Facebook that day.

Want to know when an online service is down? Keep up with outages by visiting Downdetector.

Ookla retains ownership of this article including all of the intellectual property rights, data, content graphs and analysis. This article may not be quoted, reproduced, distributed or published for any commercial purpose without prior consent. Members of the press and others using the findings in this article for non-commercial purposes are welcome to publicly share and link to report information with attribution to Ookla.

| October 17, 2023

51 New Ookla Market Reports Available for Q3 2023

Ookla® Market Reports™ identify key data about internet performance in countries across the world. This quarter we’ve provided updated analyses for 51 markets using Speedtest Intelligence® and summarized a few top takeaways below. Click through to the market report to see more details and charts about the countries you’re interested in, including the fastest fixed broadband providers and mobile operators, who had the most consistent service, and 5G and device performance in select countries during Q3 2023. Jump forward to a continent using these links:

Africa | Americas | Asia | Europe | Oceania

Africa

  • Côte d’Ivoire: Orange recorded the fastest median mobile and fixed download speeds during Q3 2023, at 24.33 Mbps and 66.84 Mbps, respectively. Moov Africa recorded the lowest median multi-server latency over fixed broadband at 122 ms. Of Côte d’Ivoire most populous cities, Bouake had the fastest median fixed download speed of 59.22 Mbps, just ahead of Abidjan with 58.44 Mbps.
  • Mozambique: There were no statistical winners for fastest median mobile download speed during Q3 2023, with Vodacom and Tmcel delivering median download speeds of 31.16 Mbps and 27.89 Mbps, respectively. Tmcel recorded the lowest mobile multi-server latency at 52 ms and the highest Consistency at 91.8%. Of Mozambique’s most populous cities, Maputo had the fastest median mobile and fixed download speeds at 28.71 Mbps and 12.57 Mbps, respectively. SpaceX’s Starlink recorded the fastest fixed broadband median download speed in Q3 2023 at 53.98 Mbps, along with the highest Consistency at 60.3%. Meanwhile, TVCABO recorded the lowest median multi-server latency over fixed broadband at 14 ms.
  • Senegal: There was no winner of fastest median mobile performance in Senegal during Q3 2023, with Orange and Free both tied. Orange led the market for median fixed broadband download performance, with 21.68 Mbps in Q3 2023. It also had the lowest median multi-server latency at 85 ms and highest Consistency of 45.3%. Of Senegal’s most populous cities, Dakar had the fastest median fixed download speed of 26.08 Mbps.

Americas

  • Argentina: Personal had the fastest median download speed over mobile at 36.63 Mbps, while also registering lowest mobile multi-server latency at 39 ms during Q3 2023. In the fixed broadband market, there was no statistically fastest network, with Movistar and Telecentro delivering median download speeds of 102.55 Mbps and 101.96 Mbps, respectively. Movistar recorded the lowest multi-server latency of 10 ms. Among Argentina’s most populous cities, La Plata recorded the fastest mobile download speed of 35.48 Mbps, while Buenos Aires recorded the fastest fixed download speed of 105.50 Mbps.
  • Belize: Digi had the fastest median mobile download and upload speeds of 17.23 Mbps and 10.38 Mbps, respectively during Q3 2023. Digi also recorded the highest Consistency of 81.5%, while smart! recorded the lowest median mobile multi-server latency of 55 ms. NEXGEN had the fastest median download and upload speeds over fixed broadband in Belize at 48.27 Mbps and 47.29 Mbps, respectively.
  • Canada: Bell was the fastest mobile operator in Canada with a median download speed of 100.77 Mbps in Q3 2023. Bell also had the fastest median 5G download speed at 183.06 Mbps. Rogers had the fastest median mobile upload speed of 11.44 Mbps, and the highest Consistency of 82.9%. Bell pure fibre was fastest for fixed broadband, recording a median download speed of 286.08 Mbps and a median upload speed of 244.64 Mbps. Of Canada’s most populous cities, St. John’s recorded the fastest median mobile download speed at 158.19 Mbps, while Fredericton recorded the fastest median fixed broadband download speed of 238.49 Mbps.
  • Colombia: Movistar was fastest for fixed broadband with a median download speed of 181.42 Mbps in Q3 2023. ETB had the lowest median multi-server latency over fixed broadband at 9 ms. Of Colombia’s most populous cities, Cartagena recorded the fastest median fixed download speed of 125.15 Mbps.
  • Costa Rica: Claro had the fastest median download and upload speeds among mobile operators at 52.38 Mbps and 12.56 Mbps, respectively. Liberty had the lowest mobile multi-server latency at 33 ms and the highest Consistency at 80.1%. Metrocom was fastest for fixed broadband download and upload performance, at 213.77 Mbps and 157.89 Mbps, respectively.
  • Dominican Republic: Claro had the fastest median download and upload speeds among mobile operators at 32.22 Mbps and 9.27 Mbps, respectively. Viva had the lowest mobile multi-server latency at 44 ms. SpaceX’s Starlink was fastest for fixed broadband download performance at 49.21 Mbps, while Claro recorded the fastest median upload speed at 14.81 Mbps, as well as the lowest multi-server latency at 40 ms. Of the Dominican Republic’s most populous cities, Santo Domingo recorded the fastest median mobile and fixed download speeds of 37.43 Mbps and 44.92 Mbps, respectively.
  • Ecuador: There was no winner of fastest median mobile performance in Ecuador during Q3 2023, with CNT and Claro posting median download speeds of 28.00 Mbps and 26.65 Mbps, respectively. Movistar recorded the lowest mobile multi-server latency, of 40 ms. Netlife was fastest for fixed broadband, with a median download speed of 90.31 Mbps. Netlife also recorded the lowest multi-server latency over fixed broadband at 8ms.
  • El Salvador: Claro had the fastest median download speed among mobile operators at 41.26 Mbps, along with the highest Consistency of 88.5%. Movistar registered the lowest median multi-server latency in El Salvador at 59 ms. Cable Color recorded the fastest median fixed download speed at 54.91 Mbps, the top median upload speed at 49.87 Mbps, and the lowest median multi-server latency of 42 ms.
  • Guatemala: Claro was the fastest mobile operator in Guatemala with a median download speed of 37.39 Mbps and a median upload speed of 20.43 Mbps. Claro also had the highest Consistency at 86.1%, while also leading the market for 5G performance, with a median 5G download speed of 370.97 Mbps. SpaceX’s Starlink was fastest for median fixed download performance at 56.91 Mbps, while Cable Color was fastest for fixed upload performance at 28.96 Mbps. Cable Color also had the lowest median multi-server latency on fixed broadband at 34 ms.
  • Guyana: There was no winner of fastest median mobile performance in Guyana during Q3 2023, with ENet and Digicel posting median download speeds of 32.48 Mbps and 28.01 Mbps, respectively. ENet recorded the fastest median mobile upload speed at 18.03 Mbps and offered the lowest median multi-server latency at 137 ms. In the fixed broadband market, ENet recorded the fastest median download and upload speeds, of 61.46 Mbps and 39.75 Mbps, respectively.
  • Haiti: Digicel was the fastest mobile operator in Haiti with a median mobile download speed of 13.77 Mbps, a median upload speed of 9.92 Mbps, and Consistency of 67.4%. SpaceX Starlink had the fastest median fixed download speed at 50.18 Mbps. Natcom had the fastest median fixed upload speed at 32.10 Mbps and the lowest median fixed multi-server latency at 41 ms.
  • Honduras: Claro had the fastest median download and upload speeds over mobile at 54.06 Mbps and 15.75 Mbps, respectively. Claro also had the lowest mobile median multi-server latency at 89 ms and highest Consistency at 88.4%. Claro recorded the fastest median fixed broadband download speed of 46.11 Mbps, while TEVISAT had the fastest median upload speed of 21.30 Mbps and lowest median multi-server latency of 32 ms.
  • Jamaica: There was no winner of fastest median mobile download performance in Jamaica during Q3 2023, with Digicel and Flow tied. Digicel recorded the fastest median upload speed of 9.55 Mbps and highest Consistency of 85.8%. Flow had the lowest mobile median multi-server latency at 36 ms. SpaceX Starlink had the fastest median download speed over fixed broadband at 79.85 Mbps.
  • Mexico: Telcel had the fastest median download speed over mobile at 50.81 Mbps, and the operator also delivered the fastest median 5G download speed at 223.06 Mbps. Telcel also had the lowest mobile median multi-server latency at 63 ms and highest Consistency at 87.1%. Totalplay was fastest for fixed broadband with a median download speed of 88.28 Mbps and upload speed of 30.60 Mbps. Totalplay also had the lowest median multi-server latency at 27 ms. Among Mexico’s most populous cities, Monterrey recorded the fastest median download speeds on both mobile and fixed, at 39.47 Mbps and 77.94 Mbps, respectively.
  • Panama: MasMovil was the fastest mobile operator with median download and upload speeds of 23.66 Mbps and 15.49 Mbps, respectively, as well as the highest Consistency of 80.6%. MasMovil was also the fastest fixed network provider, with a median download speed of 147.50 Mbps and a median upload speed of 30.12 Mbps.
  • Peru: Claro was the fastest mobile operator with a median download speed of 22.27 Mbps,and Claro also had the highest mobile Consistency in the market with 80.3%.
  • Trinidad and Tobago: Digicel had the fastest median download speed over mobile at 34.92 Mbps and highest Consistency of 89.4%. Digicel+ had the fastest median fixed broadband download and upload speeds at 114.20 Mbps and 105.21 Mbps, respectively. Digicel+ also had the lowest median multi-server latency at 7 ms, as well as the highest Video Score at 82.35.
  • United States: T-Mobile was the fastest mobile operator with a median download speed of 163.59 Mbps. T-Mobile also had the fastest median 5G download speed at 221.57 Mbps, as well as the lowest 5G multi-server latency of 50 ms. Cox led the market as the fastest fixed broadband provider with a median download speed of 260.09 Mbps, while AT&T Internet recorded the fastest median fixed upload speed of 188.60 Mbps, and Verizon had the lowest median multi-server latency on fixed broadband at 16 ms.
  • Uruguay: Antel was the fastest mobile operator with a median download speed of 182.79 Mbps, and Antel also had the lowest median multi-server latency of 42 ms.
  • Venezuela: Digitel was the fastest mobile operator with a median download speed of 13.53 Mbps and a median upload speed of 6.54 Mbps. Digitel also recorded the highest Consistency in the market, with 66.2%, and the lowest median multi-server latency of 95 ms. Airtek Solutions had the fastest fixed median download speed of 82.79 Mbps, upload speed of 88.09 Mbps, and the lowest median multi-server latency at 7 ms.

Asia

  • Afghanistan: The fastest mobile operator in Afghanistan was Afghan Wireless with a median download speed of 6.38 Mbps. The operator also had the lowest median multi-server latency at 74 ms and the highest Consistency of 52.3% in Q3 2023.
  • Bangladesh: Banglalink was the fastest mobile operator in Bangladesh with a median download speed of 25.03 Mbps in Q3 2023. Banglalink also recorded the highest Consistency of 85.3% and the lowest median multi-server latency of 35ms. DOT Internet was the fastest fixed broadband provider with a median download speed of 90.20 Mbps, while also recording the highest Consistency at 85.6% and the lowest median multi-server latency at 5 ms.
  • Bhutan: There was no statistical winner for fastest mobile download performance during Q3 2023 in Bhutan, with BT and TashiCell both tied.
  • Brunei: There was no statistical winner for fastest mobile download performance during Q3 2023 in Brunei, with DST and Imagine both tied.
  • Cambodia: Cellcard recorded the fastest median mobile download speed at 31.76 Mbps during Q3 2023, while Metfone recorded the highest Consistency at 81.0% and the lowest median multi-server latency at 38 ms. There was no statistical winner among top providers in Cambodia for median fixed download speed, with SINET and MekongNet both tied.
  • China: China Mobile was the fastest mobile operator with a median download speed of 179.81 Mbps, and highest Consistency of 95.6%. China Broadnet recorded the fastest median 5G download speed at 297.59 Mbps. China Unicom was fastest for fixed broadband at 208.59 Mbps. Among China’s most populous cities, Beijing recorded the fastest median mobile download speed of 220.21 Mbps, while Tianjin recorded the fastest median fixed download speed of 284.90 Mbps.
  • Georgia: There was no statistical winner for fastest mobile download performance during Q3 2023 in Georgia, with Geocell and Magti both tied. Geocell recorded the lowest median mobile multi-server latency at 41 ms, while Magti recorded the highest mobile Consistency with 88.0%. MagtiCom had the fastest median fixed download speed at 27.80 Mbps during Q3 2023. It also recorded the highest Consistency, of 66.3%, and the lowest median multi-server latency at 12 ms. Among Georgia’s most populous cities, Gori recorded the fastest median mobile download speed of 39.01 Mbps, while Tbilisi recorded the fastest median fixed download speed of 26.98 Mbps.
  • Indonesia: Telkomsel was the fastest Indonesian mobile operator with a median download speed of 31.04 Mbps. Telkomsel also had the lowest median mobile multi-server latency at 45 ms.
  • Japan: Rakuten Mobile recorded the fastest mobile download and upload speeds during Q3 2023 in Japan, at 46.98 Mbps and 19.34 Mbps, respectively. The operator also recorded the highest Consistency in the market at 90.4%, while SoftBank recorded the lowest median multi-server latency at 44 ms. So-net had the fastest fixed download and upload speeds, at 270.59 Mbps and 213.43 Mbps, respectively, as well as the lowest median multi-server latency over fixed broadband at 9 ms.
  • Malaysia: TIME was the fastest fixed broadband provider in Malaysia with a median download speed of 110.23 Mbps. TIME also recorded the highest Consistency in the market with 88.5% and the lowest multi-server latency at 9 ms.
  • Pakistan: Jazz delivered the fastest median mobile download speed in Pakistan at 20.63 Mbps in Q3 2023 and the highest Consistency of 80.5%. Zong recorded the lowest median mobile multi-server latency of 52 ms. Transworld had the fastest median fixed broadband download speed in Pakistan at 18.91 Mbps and the highest Consistency at 40.1%.
  • Philippines: Smart delivered the fastest median mobile download speed in the Philippines at 35.56 Mbps in Q3 2023.
  • South Korea: SK Telecom recorded the fastest median mobile download and upload speeds at 174.80 Mbps and 17.94 Mbps, respectively, while also recording the highest Consistency in the market at 86.3%. LG U+ had the lowest median mobile multi-server latency in the market at 66 ms. In South Korea’s fixed broadband market, LG U+ delivered the fastest median download and upload speeds at 148.56 Mbps and 96.53 Mbps, respectively. LG U+ also recorded the lowest median multi-server latency of 38 ms.
  • Sri Lanka: SLT-Mobitel delivered the fastest mobile and fixed download speed in Sri Lanka at 21.78 Mbps and 35.70 Mbps respectively in Q3 2023. Dialog had the lowest median mobile multi-server latency at 35 ms, while SLT-Mobitel recorded the lowest fixed broadband multi-server latency at 13 ms and the highest Consistency at 56.4%.
  • Turkey: Turkcell was the fastest mobile operator in Turkey with a median download speed of 57.60 Mbps, and the operator also recorded the highest Consistency of 90.8%. Türk Telekom had the lowest median mobile multi-server latency at 41 ms. TurkNet was fastest for fixed broadband, with a median download speed of 64.31 Mbps. TurkNet also recorded the lowest median fixed multi-server latency at 13 ms, and highest Consistency at 80.6%. Among Turkey’s most populous cities, Istanbul recorded the fastest median download speeds across mobile and fixed, of 41.22 Mbps, and 44.38 Mbps, respectively.
  • Vietnam: Vinaphone had the fastest median mobile download speed in Q3 2023, at 54.74 Mbps. Vinaphone also had the lowest median mobile multi-server latency at 34 ms and the highest Consistency at 94.7%. Viettel was the fastest fixed provider with a median download speed of 109.77 Mbps. Viettel also recorded the lowest median fixed broadband multi-server latency of 7 ms and the highest Consistency at 91.4%.

Europe

  • Albania: There was no statistical winner for fastest mobile download performance during Q3 2023 in Albania, with One Albania and Vodafone tied. One Albania recorded the highest Consistency of 84.5%, while Vodafone recorded the lowest median multi-server latency at 35 ms. Digicom was the fastest fixed broadband provider with a median download speed of 93.98 Mbps, while also recording the highest Consistency at 87.9%. Among Albania’s most populous cities, Elbasan recorded the fastest median mobile download speed of 65.31 Mbps, while Vlorë recorded the fastest median fixed download speed of 56.98 Mbps.
  • Belgium: Proximus recorded the fastest median mobile download speed during Q3 2023, at 88.76 Mbps. Proximus also recorded the highest mobile Consistency in the market at 89.4%. Telenet had the fastest median fixed download speed at 149.77 Mbps, while VOO recorded the highest Consistency at 89.2%. Among Belgium’s most populous cities, Ghent recorded the fastest median mobile download speed of 213.88 Mbps, while Antwerp offered the fastest median fixed download speed of 88.93 Mbps.
  • Denmark: YouSee was the fastest mobile operator in Denmark with a median download speed of 131.88 Mbps in Q3 2023. Hiper was fastest for fixed broadband, with a median download speed of 274.54 Mbps.
  • Estonia: The fastest mobile operator in Estonia was Telia with a median download speed of 89.65 Mbps in Q3 2023. Elisa was the fastest fixed broadband provider, with a median download speed of 97.27 Mbps, while Infonet recorded the lowest median fixed broadband multi-server latency of 5 ms.
  • Finland: DNA had the fastest median mobile download speed at 100.55 Mbps in Q3 2023 and the highest Consistency of 91.9%. Telia recorded the lowest median mobile multi-server latency of 32 ms. Lounea was fastest for fixed broadband with a median download speed of 122.03 Mbps. Lounea also recorded the highest Consistency in the market at 92.3%, as well as the lowest median fixed broadband multi-server latency at 11 ms.
  • Germany: Telekom was the fastest mobile operator in Germany during Q3 2023, with a median download speed of 91.53 Mbps, as well as the top median download speed over 5G at 182.50 Mbps. Telekom also recorded the highest Consistency in the market at 90.7% and the lowest median mobile multi-server latency of 39 ms. Deutsche Glasfaser recorded the fastest fixed broadband performance, with a median download speed at 191.89 Mbps. It also recorded the highest Consistency in the market at 89.8% and the lowest fixed broadband multi-server latency of 14 ms.
  • Latvia: BITĖ was the fastest mobile operator in Latvia during Q3 2023, with a median download speed of 81.00 Mbps and the highest Consistency in the market of 89.3%. LMT recorded the lowest mobile multi-server latency at 27 ms. Balticom was fastest for fixed broadband with a median download speed of 256.37 Mbps. Balticom also had the highest fixed broadband Consistency of 92.5% and the lowest median fixed broadband multi-server latency at 4 ms.
  • Lithuania: Telia was the fastest mobile operator in Lithuania during Q3 2023, with a median download speed of 117.76 Mbps in Q3 2023. Telia also recorded the highest Consistency in the market at 92.8%. Cgates was fastest for fixed broadband with a median download speed at 167.30 Mbps. Cgates also recorded the highest Consistency over fixed broadband in the market at 90.1%.
  • Poland: T-Mobile was the fastest mobile operator in Poland during Q3 2023, with a median download speed of 50.31 Mbps. T-Mobile also recorded the highest Consistency in the market at 86.8%. Plus recorded the fastest 5G performance in the market, with a median 5G download speed of 146.01 Mbps. UPC was the fastest provider for fixed broadband with a median download speed of 228.57 Mbps in Q3 2023. Among Poland’s most populous cities, Łódź recorded the fastest median mobile download speed of 52.92 Mbps, while Wrocław recorded the fastest median fixed download speed of 163.04 Mbps.
  • Switzerland: Salt was the fastest fixed broadband provider in Switzerland, with a median download speed of 384.65 Mbps. Salt also had the highest Consistency in the market at 94.8% and the lowest median multi-server latency over fixed broadband at 8 ms.

Oceania

  • New Zealand: One NZ was the fastest mobile operator in New Zealand during Q3 2023, with a median download speed of 74.20 Mbps. 2degrees led the market with the highest Consistency of 91.0% and the lowest median mobile multi-server latency at 41 ms.

The Speedtest Global Index is your resource to understand how internet connectivity compares around the world and how it’s changing. Check back next month for updated data on country and city rankings, and look for updated Ookla Market Reports with Q4 2023 data in January.

Ookla retains ownership of this article including all of the intellectual property rights, data, content graphs and analysis. This article may not be quoted, reproduced, distributed or published for any commercial purpose without prior consent. Members of the press and others using the findings in this article for non-commercial purposes are welcome to publicly share and link to report information with attribution to Ookla.

| May 23, 2023

U.S. Airports Have Fastest Free Airport Wi-Fi, Chinese Airports Have Faster Mobile

The summer travel season is about to officially begin across the northern hemisphere and we’re back with fresh data for our series on airport Wi-Fi performance. This year we examined mobile Wi-Fi on free Wi-Fi provided by the individual airports as well as mobile speeds at some of the busiest airports in the world during Q1 2023. While airports in the United States top the list of fastest free airport Wi-Fi, the fastest mobile speeds we saw were in China. Read on for a specific look at internet performance including: download speed, upload speed, and latency.

U.S. airports have fastest airport Wi-Fi

Speedtest Intelligence® showed two U.S. airports at the top of the list for free airport Wi-Fi with Fort Lauderdale’s Hollywood International Airport Terminal 3 and San Francisco International Airport showing median download speeds of 157.60 Mbps and 156.66 Mbps, respectively, during Q1 2023. This represented a small drop for SFO since our November analysis but an increase for FLL. Dallas/Fort Worth International Airport (143.42 Mbps), John F. Kennedy International Airport (136.06 Mbps), and Seattle–Tacoma International Airport (136.02 Mbps) rounded out the top five with three additional SSIDs from FLL following closely behind with median download speeds from 122.07 Mbps to 134.62 Mbps.

Chart of Mobile Internet Performance Over Free Wi-Fi at Select Airports

As we’ve seen in most recent analyses, the airports with the fastest Wi-Fi are international hubs that passengers from around the world pass through on their way to all kinds of destinations. If you are connecting through any of these airports, you should have no trouble with internet speeds this fast. In case of video calls, upload speeds are even faster than downloads at almost all of these airports, and SFO had the fastest uploads on the list.

Hartsfield–Jackson Atlanta International Airport and SEA had the lowest median multi-server latency on Wi-Fi of any of the airports surveyed during Q1 2023. This means your device should see very little delay when relaying information across the web.

Shanghai tops Wi-Fi performance at global airports

Shanghai Pudong International Airport was the fastest non-U.S. airport on our list with a fastest median download speed of 118.67 Mbps. Charles de Gaulle Airport in Paris (98.82 Mbps), Amsterdam Airport Schiphol (82.83 Mbps), Dubai International Airport (67.21 Mbps), and Frankfurt Airport (59.10 Mbps) followed for median download speeds at non-U.S. airports. All of these airports have internet speeds that qualify as at least good, which means you should be okay unless you want to try multi-player gaming (which is probably not your first choice on an airport layover anyway). Both Mexican airports on our list showed speeds in the slow range, so log off early and enjoy your vacation if you’re at the airport in Cancún or Mexico City.

Chinese airports have fastest mobile speeds

Get ready to connect to local mobile service or tether your phone to your laptop if you’re traveling through airports in Shanghai and Beijing and have access to 5G. Not only did Shanghai Pudong International Airport, Beijing Capital International Airport, and Beijing Daxing International Airport have the fastest median downloads over mobile on our list at 308.51 Mbps, 304.87 Mbps, and 300.70 Mbps, respectively, during Q1 2023 — the mobile speeds at these airports were dramatically faster than the airport Wi-Fi. Salt Lake City International Airport (282.21 Mbps) and Hangzhou Xiaoshan International Airport (259.86 Mbps) rounded out the top five.

Chart of Mobile Network Performance at Select Airports

While latency on mobile was generally higher than that on Wi-Fi, these same three Chinese airports (PEK, PKX, and PVG) also showed the lowest median multi-server latency on mobile during Q1 2023, indicating that your internet experience at these airports will have the least lag. Airports outside the U.S. performed better for latency overall with the top 16 airports for latency all located outside North America. CUN had the highest latency on mobile.

We were able to include more airports in the mobile analysis because there were more mobile samples to analyze at those airports than there were samples over Wi-Fi.

Airport Wi-Fi or mobile? Connecting on your next trip

Save yourself time by using this checklist to decide whether to try out the Wi-Fi or simply use the local mobile network. We compared internet performance on free airport Wi-Fi with median download speeds over mobile for the 38 airports we have both Wi-Fi and mobile data for during Q1 2023. Twenty-one airports had faster mobile internet than airport Wi-Fi. Twelve airports had faster Wi-Fi than mobile, and four airports showed only a slight distinction between Wi-Fi and mobile so we gave both the green check marks.

Chart Comparing Airport Wi-Fi and Mobile Speeds at Select Airports

Airport Wi-Fi has come a long way since we started this series in 2017. We hope your connections are smooth and if you’re traveling this summer, take a Speedtest® at the airport to see how your experience compares.

Ookla retains ownership of this article including all of the intellectual property rights, data, content graphs and analysis. This article may not be quoted, reproduced, distributed or published for any commercial purpose without prior consent. Members of the press and others using the findings in this article for non-commercial purposes are welcome to publicly share and link to report information with attribution to Ookla.

| January 21, 2021

New Year, Great Data: The Best Ookla Open Data Projects We’ve Seen So Far


When we announced Ookla® Open Datasets from Ookla For Good™ in October, we were hoping to see exciting projects that raise the bar on the conversation about internet speeds and accessibility — and you delivered. From analyses of internet inequity in the United States to measures of data affluence in India, today we’re highlighting four projects that really show what this data can do. We also have a new, simpler tutorial on how you can use this data for your own efforts to improve the state of networks worldwide.

Highlighting the digital divide in the U.S.

Jamie Saxon with the Center for Data and Computing at the University of Chicago married Ookla data on broadband performance with data from the American Community Survey to create interactive maps of the digital divide in 20 U.S. cities. These maps provide views into many variables that contribute to internet inequities.

Ookla_open_datasets_James_Saxon_0121-1

Building a data affluence map

Raj Bhagat P shows how different variables can be combined with this map of data affluence that combines data on internet speeds and device counts in India.

Ookla_open_datasets_Raj-Bhagat-P_0121-1

Internet speeds are beautiful

This map of fixed broadband speeds across Europe from Boris Mericskay shows that internet performance can be as visually stunning as a map of city lights.

Ookla_open_datasets_Boris-Mericskay_0121-1

Topi Tjunakov created a similar image of internet speeds in and around Japan.

Ookla_open_datasets_Topi-Tjunakov_0121-1

Use Ookla Open Datasets to make your own maps

This section will demonstrate a few possible ways to use Ookla Open Datasets using the United Kingdom as an example. The ideas can be adapted for any area around the world. This tutorial uses the R programming language, but there are also Python tutorials available in the Ookla Open Data GitHub repository.

library(tidyverse)
library(patchwork)
library(janitor)
library(ggrepel)
library(usethis)
library(lubridate)
library(colorspace)
library(scales)
library(kableExtra)
library(knitr)
library(sf)

# colors for plots
purple <- "#A244DA"
light_purple <- colorspace::lighten("#A244DA", 0.5)
green <- colorspace::desaturate("#2DE5D1", 0.2)
blue_gray <- "#464a62"
mid_gray <- "#ccd0dd"
light_gray <- "#f9f9fd"

# set some global theme defaults
theme_set(theme_minimal())
theme_update(text = element_text(family = "sans", color = "#464a62"))
theme_update(plot.title = element_text(hjust = 0.5, face = "bold"))
theme_update(plot.subtitle = element_text(hjust = 0.5))

Ookla Open Datasets include quarterly performance and test count data for both mobile networks and fixed broadband aggregated over all providers. The tests are binned into global zoom level 16 tiles which can be thought of as roughly a few football fields. As of today, all four quarters of 2020 are available and subsequent quarters will be added as they complete.

Administrative unit data

I chose to analyse the mobile data at the Nomenclature of Territorial Units for Statistics (NUTS) 3 level (1:1 million). These administrative units are maintained by the European Union to allow for comparable analysis across member states. NUTS 3 areas mean:

  • In England, upper tier authorities and groups of unitary authorities and districts
  • In Wales, groups of Principal Areas
  • In Scotland, groups of Council Areas or Islands Areas
  • In Northern Ireland, groups of districts

To make a comparison to the U.S. administrative structure, these can be roughly thought of as the size of counties. Here is the code you’ll want to use to download the NUTS shapefiles from the Eurostat site. Once the zipfile is downloaded you will need to unzip it again in order to read it into your R environment:

# create a directory called “data”
dir.create("data")
use_zip("https://gisco-services.ec.europa.eu/distribution/v2/nuts/download/ref-nuts-2021-01m.shp.zip", destdir = "data")

uk_nuts_3 <- read_sf("data/ref-nuts-2021-01m.shp/NUTS_RG_01M_2021_3857_LEVL_3.shp/NUTS_RG_01M_2021_3857_LEVL_3.shp") %>%
  filter(CNTR_CODE == "UK") %>%
  st_transform(4326) %>%
  clean_names() %>%
  mutate(urbn_desc = case_when( # add more descriptive labels for urban variable
    urbn_type == 1 ~ "Urban",
    urbn_type == 2 ~ "Intermediate",
    urbn_type == 3 ~ "Rural"
  ),
  urbn_desc = factor(urbn_desc, levels = c("Urban", "Intermediate", "Rural")))

# contextual city data
uk_cities <- read_sf("https://opendata.arcgis.com/datasets/6996f03a1b364dbab4008d99380370ed_0.geojson") %>%
  clean_names() %>%
  filter(fips_cntry == "UK", pop_rank <= 5)

ggplot(uk_nuts_3) +
  geom_sf(color = mid_gray, fill = light_gray, lwd = 0.08) +
  geom_text_repel(data = uk_cities, 
                           aes(label = city_name, geometry = geometry), 
                           family = "sans", 
                           color = blue_gray, 
                           size = 2.2, 
                           stat = "sf_coordinates",
                           min.segment.length = 2) +
  labs(title = "United Kingdom",
       subtitle = "NUTS 3 Areas") +
  theme(panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        axis.text = element_blank(),
        axis.title = element_blank())

plot_uk-1-1

Adding data from Ookla Open Datasets

You’ll want to crop the global dataset to the bounding box of the U.K. This will include some extra tiles (within the box but not within the country, i.e. some of western Ireland), but it makes the data much easier to work with later on.

uk_bbox <- uk_nuts_3 %>%
  st_union() %>% # otherwise would be calculating the bounding box of each individual area
  st_bbox()
  

Each of the quarters are stored in separate shapefiles. You can read them in one-by-one and crop them to the U.K. box in the same pipeline.

# download the data with the following code:

use_zip("https://ookla-open-data.s3.amazonaws.com/shapefiles/performance/type=mobile/year=2020/quarter=1/2020-01-01_performance_mobile_tiles.zip", destdir = "data")
use_zip("https://ookla-open-data.s3.amazonaws.com/shapefiles/performance/type=mobile/year=2020/quarter=2/2020-04-01_performance_mobile_tiles.zip", destdir = "data")
use_zip("https://ookla-open-data.s3.amazonaws.com/shapefiles/performance/type=mobile/year=2020/quarter=3/2020-07-01_performance_mobile_tiles.zip", destdir = "data")
use_zip("https://ookla-open-data.s3.amazonaws.com/shapefiles/performance/type=mobile/year=2020/quarter=4/2020-10-01_performance_mobile_tiles.zip", destdir = "data")

# and then read in those downloaded files
mobile_tiles_q1 <- read_sf("data/2020-01-01_performance_mobile_tiles/gps_mobile_tiles.shp") %>%
  st_crop(uk_bbox)
mobile_tiles_q2 <- read_sf("data/2020-04-01_performance_mobile_tiles/gps_mobile_tiles.shp") %>%
  st_crop(uk_bbox)
mobile_tiles_q3 <- read_sf("data/2020-07-01_performance_mobile_tiles/gps_mobile_tiles.shp") %>%
  st_crop(uk_bbox)
mobile_tiles_q4 <- read_sf("data/2020-10-01_performance_mobile_tiles/gps_mobile_tiles.shp") %>%
  st_crop(uk_bbox)

As you see, the tiles cover most of the area, with more tiles in more densely populated areas. (And note that you still have tiles included that are outside the boundary of the area but within the bounding box.)

ggplot(uk_nuts_3) +
  geom_sf(color = mid_gray, fill = light_gray, lwd = 0.08) +
  geom_sf(data = mobile_tiles_q4, fill = purple, color = NA) +
  geom_text_repel(data = uk_cities, 
                           aes(label = city_name, geometry = geometry), 
                           family = "sans", 
                           color = blue_gray, 
                           size = 2.2, 
                           stat = "sf_coordinates",
                           min.segment.length = 2) +
  labs(title = "United Kingdom",
       subtitle = "Ookla® Open Data Mobile Tiles, NUTS 3 Areas") +
  theme(panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        axis.text = element_blank(),
        axis.title = element_blank())

tile_map-1-3

Now that the cropped tiles are read in, you’ll use a spatial join to determine which NUTS 3 area each tile is in. In this step, I am also reprojecting the data to the British National Grid (meters). I’ve also added a variable to identify the time period (quarter).

tiles_q1_nuts <- uk_nuts_3 %>%
  st_transform(27700) %>% # British National Grid
  st_join(mobile_tiles_q1 %>% st_transform(27700), left = FALSE) %>%
  mutate(quarter_start = "2020-01-01")

tiles_q2_nuts <- uk_nuts_3 %>%
  st_transform(27700) %>%
  st_join(mobile_tiles_q2 %>% st_transform(27700), left = FALSE) %>%
  mutate(quarter_start = "2020-04-01")

tiles_q3_nuts <- uk_nuts_3 %>%
  st_transform(27700) %>%
  st_join(mobile_tiles_q3 %>% st_transform(27700), left = FALSE) %>%
  mutate(quarter_start = "2020-07-01")

tiles_q4_nuts <- uk_nuts_3 %>%
  st_transform(27700) %>%
  st_join(mobile_tiles_q4 %>% st_transform(27700), left = FALSE) %>%
  mutate(quarter_start = "2020-10-01")

In order to make the data easier to work with, combine the tiles into a long dataframe with each row representing one tile in one quarter. The geometry now represents the NUTS region, not the original tile shape.

tiles_all <- tiles_q1_nuts %>%
  rbind(tiles_q2_nuts) %>%
  rbind(tiles_q3_nuts) %>%
  rbind(tiles_q4_nuts) %>%
  mutate(quarter_start = ymd(quarter_start)) # convert to date format

With this dataframe, you can start to generate some aggregates. In this table you’ll include the tile count, test count, quarter and average download and upload speeds.

Exploratory data analysis

aggs_quarter <- tiles_all %>%
  st_set_geometry(NULL) %>%
  group_by(quarter_start) %>%
  summarise(tiles = n(),
            avg_d_mbps = weighted.mean(avg_d_kbps / 1000, tests), # I find Mbps easier to work with
            avg_u_mbps = weighted.mean(avg_u_kbps / 1000, tests),
            tests = sum(tests)) %>%
  ungroup()


knitr::kable(aggs_quarter) %>%
  kable_styling()

aggregates_table_kj

We can see from this table that both download and upload speeds increased throughout the year, with a small dip in upload speeds in Q2. Next, you’ll want to plot this data.

ggplot(aggs_quarter, aes(x = quarter_start)) +
  geom_point(aes(y = avg_d_mbps), color = purple) +
  geom_line(aes(y = avg_d_mbps), color = purple, lwd = 0.5) +
  geom_text(aes(y = avg_d_mbps - 2, label = round(avg_d_mbps, 1)), color = purple, size = 3, family = "sans") +
  geom_text(data = NULL, x = ymd("2020-02-01"), y = 47, label = "Download speed", color = purple, size = 3, family = "sans") +
  geom_point(aes(y = avg_u_mbps), color = light_purple) +
  geom_line(aes(y = avg_u_mbps), color = light_purple, lwd = 0.5) +
  geom_text(aes(y = avg_u_mbps - 2, label = round(avg_u_mbps, 1)), color = light_purple, size = 3, family = "sans") +
  geom_text(data = NULL, x = ymd("2020-02-05"), y = 14, label = "Upload speed", color = light_purple, size = 3, family = "sans") +
  labs(y = "", x = "Quarter start date",
       title = "Mobile Network Performance, U.K.",
       subtitle = "Ookla® Open Datasets | 2020") +
  theme(panel.grid.minor = element_blank(),
        panel.grid.major = element_blank(),
        axis.title.x = element_text(hjust=1)) +
  scale_y_continuous(labels = label_number(suffix = " Mbps", scale = 1, accuracy = 1)) +
  scale_x_date(date_labels = "%b %d")

line_up_down-1

Examining test counts

We also saw above that the number of tests decreased between Q1 and Q2 and then peaked in Q3 at a little over 700,000 before coming back down. The increase likely followed resulted from interest in network performance during COVID-19 when more people started working from home. This spike is even more obvious in chart form.

ggplot(aggs_quarter, aes(x = quarter_start)) +
  geom_point(aes(y = tests), color = purple) +
  geom_line(aes(y = tests), color = purple, lwd = 0.5) +
  geom_text(aes(y = tests - 6000, label = comma(tests), x= quarter_start + 5), size = 3, color = purple) +
  labs(y = "", x = "Quarter start date",
       title = "Mobile Test Count, U.K.",
       subtitle = "Ookla® Open Datasets | 2020") +
  theme(panel.grid.minor = element_blank(),
        panel.grid.major = element_blank(),
        axis.title.x = element_text(hjust=1),
        axis.text = element_text(color = blue_gray)) +
  scale_y_continuous(labels = comma) +
  scale_x_date(date_labels = "%b %d")

line_tests-1-1

Data distribution

Next, I wanted to check the distribution of average download speeds.

ggplot(tiles_all) + 
  geom_histogram(aes(x = avg_d_kbps / 1000, group = quarter_start), size = 0.3, color = light_gray, fill = green) + 
  scale_x_continuous(labels = label_number(suffix = " Mbps", accuracy = 1)) +
  scale_y_continuous(labels = comma) +
  facet_grid(quarter_start ~ .) +
  theme(panel.grid.minor = element_blank(), 
        panel.grid.major = element_blank(), 
        axis.title.x = element_text(hjust=1),
        axis.text = element_text(color = blue_gray),
        strip.text.y = element_text(angle = 0, color = blue_gray)) + 
  labs(y = "", x = "", title = "Mobile Download Speed Distribution by Tile, U.K.", 
       subtitle = "Ookla® Open Datasets | 2020")

histogram-1-1

The underlying distribution of average download speeds across the tiles has stayed fairly stable.

Mapping average speed

Making a quick map of the average download speed in each region across the U.K. is relatively simple.

# generate aggregates table
nuts_3_aggs <- tiles_all %>%
  group_by(quarter_start, nuts_id, nuts_name, urbn_desc, urbn_type) %>%
  summarise(tiles = n(),
            avg_d_mbps = weighted.mean(avg_d_kbps / 1000, tests), # I find Mbps easier to work with
            avg_u_mbps = weighted.mean(avg_u_kbps / 1000, tests),
            tests = sum(tests)) %>%
  ungroup()
ggplot(nuts_3_aggs %>% filter(quarter_start == "2020-10-01")) +
  geom_sf(aes(fill = avg_d_mbps), color = blue_gray, lwd = 0.08) +
  scale_fill_stepsn(colors = RColorBrewer::brewer.pal(n = 5, name = "BuPu"), labels = label_number(suffix = " Mbps"), n.breaks = 4, guide = guide_colorsteps(title = "")) +
  theme(panel.grid.minor = element_blank(),
        panel.grid.major = element_blank(),
        axis.title.x = element_text(hjust=1),
        legend.text = element_text(color = blue_gray),
        axis.text = element_blank()) +
  labs(title = "Mobile Download Speed, U.K.", subtitle = "Ookla® Open Datasets | Q4 2020")

choropleth-1-1

As you can see, the areas around large cities have faster download speeds on average and the lowest average download speeds are typically in more rural areas.

Rural and urban analysis

People are often interested in the difference between mobile networks in urban and rural areas. The Eurostat NUTS data includes an urban indicator with three levels: rural, intermediate and urban. This typology is determined primarily by population density and proximity to a population center.

ggplot(uk_nuts_3) +
  geom_sf(aes(fill = urbn_desc), color = light_gray, lwd = 0.08) +
  geom_text_repel(data = uk_cities, 
                           aes(label = city_name, geometry = geometry), 
                           family = "sans", 
                           color = "#1a1b2e", 
                           size = 2.2, 
                           stat = "sf_coordinates",
                           min.segment.length = 2) +
  scale_fill_manual(values = c(purple, light_purple, green), name = "", guide = guide_legend(direction = "horizontal", label.position = "top", keywidth = 3, keyheight = 0.5)) +
  labs(title = "U.K., NUTS 3 Areas") +
  theme(panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        axis.text = element_blank(),
        axis.title = element_blank(),
        legend.position = "top")

rural_urban_reference-1

Data distribution overall and over time

When you aggregate by the urban indicator variable different patterns come up in the data.

# generate aggregates table
rural_urban_aggs <- tiles_all %>%
  st_set_geometry(NULL) %>%
  group_by(quarter_start, urbn_desc, urbn_type) %>%
  summarise(tiles = n(),
            avg_d_mbps = weighted.mean(avg_d_kbps / 1000, tests), # I find Mbps easier to work with
            avg_u_mbps = weighted.mean(avg_u_kbps / 1000, tests),
            tests = sum(tests)) %>%
  ungroup()

As you might expect, the download speeds during Q4 are faster in urban areas than in rural areas – with the intermediate ones somewhere in between. This pattern holds for other quarters as well.

ggplot(rural_urban_aggs %>% filter(quarter_start == "2020-10-01"), aes(x = avg_d_mbps, y = urbn_desc, fill = urbn_desc)) +
  geom_col(width = .3, show.legend = FALSE) +
  geom_jitter(data = nuts_3_aggs, aes(x = avg_d_mbps, y = urbn_desc, color = urbn_desc), size = 0.7) + 
  geom_text(aes(x = avg_d_mbps - 4, label = round(avg_d_mbps, 1)), family = "sans",  size = 3.5, color = blue_gray) +
  scale_fill_manual(values = c(purple, light_purple, green)) +
  scale_color_manual(values = darken(c(purple, light_purple, green))) +
  scale_x_continuous(labels = label_number(suffix = " Mbps", scale = 1, accuracy = 1)) +
  theme(panel.grid.minor = element_blank(),
        panel.grid.major = element_blank(),
        axis.title.x = element_text(hjust=1),
        legend.position = "none",
        axis.text = element_text(color = blue_gray)) +
  labs(y = "", x = "", 
       title = "Mobile Download Speed Distribution by NUTS 3 Area, U.K.", 
       subtitle = "Ookla® Open Datasets | 2020")  

rural_urban_bar-1-2
Interestingly though, the patterns differ when you look at a time series plot. Urban mobile networks steadily improve, while the intermediate and rural areas saw slower average download speeds starting in Q2 before going back up after Q3. This is likely the result of increased pressure on the networks during stay-at-home orders (although this graph is not conclusive evidence of that).

ggplot(rural_urban_aggs) +
  geom_line(aes(x = quarter_start, y = avg_d_mbps, color = urbn_desc)) +
  geom_point(aes(x = quarter_start, y = avg_d_mbps, color = urbn_desc)) +
  # urban label
  geom_text(data = NULL, x = ymd("2020-02-01"), y = 50, label = "Urban", color = purple, family = "sans", size = 3) +
  # intermediate label
  geom_text(data = NULL, x = ymd("2020-02-15"), y = 35, label = "Intermediate", color = light_purple, family = "sans", size = 3) +
  # rural label
  geom_text(data = NULL, x = ymd("2020-01-15"), y = 26, label = "Rural", color = green, family = "sans", size = 3) +
  scale_color_manual(values = c(purple, light_purple, green)) +
  scale_x_date(date_labels = "%b %d") +
  scale_y_continuous(labels = label_number(suffix = " Mbps", scale = 1, accuracy = 1)) +
  theme(panel.grid.minor = element_blank(),
        panel.grid.major = element_blank(),
        axis.title.x = element_text(hjust=1),
        legend.position = "none",
        axis.text = element_text(color = blue_gray)) +
  labs(y = "", x = "Quarter start date", 
       title = "Mobile Download Speed by NUTS 3 Urban-Rural Type, U.K.", 
       subtitle = "Ookla® Open Datasets | 2020") 

rural_urban_line-1-1

When you repeat the same plot but map the test count to the site of the point, you can see why the overall download speed increased steadily. The number of tests in urban areas is much higher than in intermediate and rural areas, thus pulling up the overall average.

ggplot(rural_urban_aggs) +
  geom_line(aes(x = quarter_start, y = avg_d_mbps, color = urbn_desc)) +
  geom_point(aes(x = quarter_start, y = avg_d_mbps, color = urbn_desc, size = tests)) +
  # urban label
  geom_text(data = NULL, x = ymd("2020-02-01"), y = 50, label = "Urban", color = purple, family = "sans", size = 3) +
  # intermediate label
  geom_text(data = NULL, x = ymd("2020-02-15"), y = 35, label = "Intermediate", color = light_purple, family = "sans", size = 3) +
  # rural label
  geom_text(data = NULL, x = ymd("2020-01-15"), y = 26, label = "Rural", color = green, family = "sans", size = 3) +
  scale_color_manual(values = c(purple, light_purple, green)) +
  scale_x_date(date_labels = "%b %d") +
  scale_y_continuous(labels = label_number(suffix = " Mbps", scale = 1, accuracy = 1)) +
  theme(panel.grid.minor = element_blank(),
        panel.grid.major = element_blank(),
        axis.title.x = element_text(hjust=1),
        legend.position = "none",
        axis.text = element_text(color = blue_gray)) +
  labs(y = "", x = "Quarter start date", 
       title = ("Mobile Download Speed by NUTS 3 Urban-Rural Type, U.K."), 
       subtitle = "Ookla® Open Datasets | 2020",
       caption = "Circle size indicates test count")  

rural_urban_line_size-1-1

Spotlighting regional variances

Parsing the data by specific geographies can reveal additional information.

bottom_20_q4 <- nuts_3_aggs %>% 
  filter(quarter_start == "2020-10-01") %>% 
  top_n(n = -20, wt = avg_d_mbps) %>%
  mutate(nuts_name = fct_reorder(factor(nuts_name), -avg_d_mbps))
map <- ggplot() +
  geom_sf(data = uk_nuts_3, fill = light_gray, color = mid_gray, lwd = 0.08) +
  geom_sf(data = bottom_20_q4, aes(fill = urbn_desc), color = mid_gray, lwd = 0.08, show.legend = FALSE) +
  geom_text_repel(data = uk_cities, 
                           aes(label = city_name, geometry = geometry), 
                           family = "sans", 
                           color = blue_gray, 
                           size = 2.2, 
                           stat = "sf_coordinates",
                           min.segment.length = 2) +
  scale_fill_manual(values = c(purple, light_purple, green), name = "", guide = guide_legend(direction = "horizontal", label.position = "top", keywidth = 3, keyheight = 0.5)) +
  labs(title = NULL,
       subtitle = NULL) +
  theme(panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        axis.text = element_blank(),
        axis.title = element_blank(),
        legend.position = "top")
barplot <- ggplot(data = bottom_20_q4, aes(x = avg_d_mbps, y = nuts_name, fill = urbn_desc)) +
  geom_col(width = .5) +
  scale_fill_manual(values = c(purple, light_purple, green), guide = guide_legend(direction = "horizontal", label.position = "top", keywidth = 3, keyheight = 0.5, title = NULL)) +
  scale_x_continuous(labels = label_number(suffix = " Mbps", scale = 1, accuracy = 1)) +
  theme(panel.grid.minor = element_blank(),
        panel.grid.major = element_blank(),
        axis.title.x = element_text(hjust=1),
        legend.position = "top",
        axis.text = element_text(color = blue_gray)) +
  labs(y = "", x = "", 
       title = ("Slowest 20 NUTS 3 Areas by Download Speed, U.K."), 
       subtitle = "Ookla® Open Datasets | Q4 2020") 
# use patchwork to put it all together
barplot + map

bottom_20-1-2
Among the 20 areas with the lowest average download speed in Q4 2020 there were three urban areas and six intermediate. The rest were rural.

top_20_q4 <- nuts_3_aggs %>% 
  filter(quarter_start == "2020-10-01") %>% 
  top_n(n = 20, wt = avg_d_mbps) %>%
  mutate(nuts_name = fct_reorder(factor(nuts_name), avg_d_mbps))
top_map <- ggplot() +
  geom_sf(data = uk_nuts_3, fill = light_gray, color = mid_gray, lwd = 0.08) +
  geom_sf(data = top_20_q4, aes(fill = urbn_desc), color = mid_gray, lwd = 0.08, show.legend = FALSE) +
  geom_text_repel(data = uk_cities, 
                           aes(label = city_name, geometry = geometry), 
                           family = "sans", 
                           color = blue_gray, 
                           size = 2.2, 
                           stat = "sf_coordinates",
                           min.segment.length = 2) +
  scale_fill_manual(values = c(purple, light_purple, green), name = "", guide = guide_legend(direction = "horizontal", label.position = "top", keywidth = 3, keyheight = 0.5)) +
  labs(title = NULL,
       subtitle = NULL) +
  theme(panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        axis.text = element_blank(),
        axis.title = element_blank(),
        legend.position = "top")
top_barplot <- ggplot(data = top_20_q4, aes(x = avg_d_mbps, y = nuts_name, fill = urbn_desc)) +
  geom_col(width = .5) +
  scale_fill_manual(values = c(purple, light_purple, green), guide = guide_legend(direction = "horizontal", label.position = "top", keywidth = 3, keyheight = 0.5, title = NULL)) +
  scale_x_continuous(labels = label_number(suffix = " Mbps", scale = 1, accuracy = 1), breaks = c(50, 100)) +
  theme(panel.grid.minor = element_blank(),
        panel.grid.major = element_blank(),
        axis.title.x = element_text(hjust=1),
        legend.position = "top",
        axis.text = element_text(color = blue_gray)) +
  labs(y = "", x = "", 
       title = "Fastest 20 NUTS 3 Areas by Mobile Download Speed, U.K.", 
       subtitle = "Ookla® Open Datasets | Q4 2020") 
top_london <- ggplot() +
  geom_sf(data = uk_nuts_3 %>% filter(str_detect(fid, "UKI")), fill = light_gray, color = mid_gray, lwd = 0.08) +
  geom_sf(data = top_20_q4 %>% filter(str_detect(nuts_id, "UKI")), aes(fill = urbn_desc), color = mid_gray, lwd = 0.08, show.legend = FALSE) +
  geom_text_repel(data = uk_cities %>% filter(city_name == "London"), 
                           aes(label = city_name, geometry = geometry), 
                           family = "sans", 
                           color = "black", 
                           size = 2.2, 
                           stat = "sf_coordinates",
                           min.segment.length = 2) +
  scale_fill_manual(values = c(purple, light_purple, green), name = "", guide = guide_legend(direction = "horizontal", label.position = "top", keywidth = 3, keyheight = 0.5)) +
  labs(title = NULL,
       subtitle = NULL) +
  theme(panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        axis.text = element_blank(),
        axis.title = element_blank(),
        legend.position = "top",
        panel.border = element_rect(colour = blue_gray, fill=NA, size=0.5))
top_map_comp <- top_map + inset_element(top_london, left = 0.6, bottom = 0.6, right = 1, top = 1)

top_barplot + top_map_comp

top_20-1-1
Meanwhile, all of the fastest 20 NUTS 3 areas were urban.

What else you can do with this data

Don’t forget there are also more tutorials with examples written in Python and R. Aside from what I showed here, you could do an interesting analysis looking at clustering patterns, sociodemographic variables and other types of administrative units like legislative or school districts.

We hope this tutorial will help you use Ookla’s open data for your own projects. Please tag us if you share your projects on social media using the hashtag #OoklaForGood so we can learn from your analyses.

Ookla retains ownership of this article including all of the intellectual property rights, data, content graphs and analysis. This article may not be quoted, reproduced, distributed or published for any commercial purpose without prior consent. Members of the press and others using the findings in this article for non-commercial purposes are welcome to publicly share and link to report information with attribution to Ookla.

| March 14, 2019

Ditch the Lag: Cities with Great Gaming Culture and Low Ping

Yes, you can game from anywhere with an internet connection. But if you’re at all competitive, it’s nice to play from somewhere with low ping and fast internet speeds. Plus when you need to leave the house, it’s extra nice to know you’re also surrounded by gamer culture. We’ve examined February 2019 Speedtest results in 35 cities that are known for their esports events, gaming conferences, game companies and more to find out who has the advantage and ranked them based on their ping.

The top contenders

Eleven_Gaming_Cities_0219

First place Bucharest, Romania is home to super-low ping, a lightning fast download speed and a thriving gaming culture. From Bucharest Gaming Week (which includes the CS:GO Southeast Europe Championship and the FIFA National Tournament) to their numerous local game studios, Bucharest is a great place to be a gamer whether you’re online or out and about.

The next five gaming cities with the lowest pings are all in Asia. Hangzhou, China comes in second overall with a fast ping and world-class download speeds. This city is so devoted to its gamers that it opened a $280 million gaming “city” in 2018 and plans 14 new esports arenas before 2022. Coming in third, Chengdu, China has an equally low ping to our first two contenders and serves as one of two host locations in China for the Global Mobile Game Confederation (GMGC). Both Hangzhou and Chengdu are also franchise holders in the Overwatch League, giving local gaming fans something to cheer about. Fourth place Singapore, host of the 5th Annual GameStart Convention in October 2018, had only a slightly slower ping than the first four cities and the fastest download speed of any of the cities we considered.

South Korea is home to the fifth and sixth best cities for gamers. A satellite city of Seoul, Seongnam-si boasts the Pangyo Techno Valley (a.k.a. the Silicon Valley of Korea) and numerous game development companies. Perfect for a city with a 9 ms ping. Though Incheon’s ping was a little slower at 12 ms, gamers there can console themselves with the city’s gamer cred — the 2018 League of Legends World Championship was held in Incheon’s Munhak Stadium.

Coming in at number seven, Budapest, Hungary is an emerging game city, having hosted its first big esports event (the V4 Future Sports Festival) in 2018, but a 12 ms ping makes them a strong contender. More established Malmö, Sweden is number eight with a slightly slower average download speed but the city is headquarters to Massive Entertainment, creators of Tom Clancy’s The Division series, Far Cry 3, Assassin’s Creed: Revelations and many more.

Vancouver, Canada, North America’s only qualifier for the top gaming cities list, comes in at number nine with a 12 ms ping and many gaming companies including the Canadian arms of Nintendo of Canada and EA (Electronic Arts). We included both Shanghai, China and Moscow, Russia on the top gamer cities list as both had a 12 ms ping as well, though the internet speeds in Shanghai are superior. Shanghai will also host the International Dota 2 in 2019 while Moscow is known for Epicenter.

The rest of the pack

Notably absent from the list above is most of the western hemisphere. Cities in North America were held back by their high pings. Cities in South America suffered from high pings and also slow internet speeds — something that esports leagues have complained is a barrier to investment.

Our full list of gaming cities provides wider geographical representation, even if the internet performance is not always as stellar. You’ll find Los Angeles in 27th place, behind Seattle, Boston and Las Vegas. And São Paulo, Brazil has the best showing in Latin America at 23rd.

Internet Performance in 35 Cities with a Gaming Culture
Speedtest Results | February 2019
City Ping (ms) Mean Download (Mbps) Mean Upload (Mbps)
Bucharest, Romania 8 172.13 126.57
Hangzhou, China 8 125.93 29.54
Chengdu, China 8 101.92 33.80
Singapore 9 196.43 200.08
Seongnam-si, South Korea 9 155.25 114.83
Incheon, South Korea 12 139.84 102.91
Budapest, Hungary 12 132.72 54.46
Malmö, Sweden 12 126.28 105.67
Vancouver, Canada 12 117.55 50.23
Shanghai, China 12 75.14 30.06
Moscow, Russia 12 64.56 63.59
Oslo, Norway 13 115.46 69.03
Hong Kong, Hong Kong (SAR) 14 167.59 161.14
Zürich, Switzerland 14 144.36 109.39
Seattle, United States 15 138.50 79.88
Stockholm, Sweden 15 134.16 93.83
Auckland, New Zealand 15 92.05 53.30
Toronto, Canada 16 134.75 67.42
Boston, United States 17 152.42 60.87
Las Vegas, United States 17 141.69 41.22
Chennai, India 17 48.40 42.93
Cologne, Germany 18 63.77 18.36
São Paulo, Brazil 18 46.43 21.57
Jakarta, Indonesia 18 17.88 10.21
Mumbai, India 19 23.40 19.26
Paris, France 20 161.04 93.68
Los Angeles, United States 20 121.00 23.57
London, United Kingdom 20 63.58 23.18
Rio de Janeiro, Brazil 20 36.50 13.33
Buenos Aires, Argentina 21 34.31 6.40
Katowice, Poland 22 83.99 20.91
Mexico City, Mexico 25 37.66 15.39
Sydney, Australia 25 34.20 9.61
Santiago, Chile 26 56.13 18.49
Tokyo, Japan 28 99.24 101.90

Of course, die-hard gamers will know that a low ping in your city won’t necessarily save you if you’re playing on a distant server.

What’s the ping like in your city? Take a Speedtest and see if your connection is hurting your gameplay.

Ookla retains ownership of this article including all of the intellectual property rights, data, content graphs and analysis. This article may not be quoted, reproduced, distributed or published for any commercial purpose without prior consent. Members of the press and others using the findings in this article for non-commercial purposes are welcome to publicly share and link to report information with attribution to Ookla.

| July 17, 2023

48 New Ookla Market Reports Available for Q2 2023

Ookla® Market Reports™ identify key data about internet performance in countries across the world. This quarter we’ve provided updated analyses for 48 markets using Speedtest Intelligence® and summarized a few top takeaways below. Click through to the market report to see more details and charts about the countries you’re interested in, including the fastest fixed broadband providers and mobile operators, who had the most consistent service, and 5G and device performance in select countries during Q2 2023. Jump forward to a continent using these links:

Africa | Americas | Asia | Europe | Oceania

Africa

  • Cameroon: Speedtest Intelligence data showed no winner for fastest mobile operator in Cameroon during Q2 2023. blue had the lowest median mobile multi-server latency at 191 ms, while Douala had the fastest median mobile download speed among Cameroon’s most populous cities at 15.51 Mbps.
  • Ethiopia: Safaricom had the fastest median mobile download speed at 35.19 Mbps during Q2 2023. Safaricom also recorded the lowest median mobile multi-server latency at 42 ms, and highest Consistency of 89.4%. Of Ethiopia’s most populous cities, Gondar had the fastest median mobile download speed of 61.22 Mbps.
  • Tanzania: There were no winners over fastest mobile or fixed broadband in Tanzania during Q2 2023. Maisha Broadband registered the lowest median multi-server latency in Tanzania at 14 ms. Of Tanzania’s most populous cities, Dar es Salaam had the fastest median mobile download speed of 26.33 Mbps, while Mbeya had the fastest median fixed download speed of 21.32 Mbps.

Americas

  • Argentina: Personal had the fastest median download speed over mobile (35.05 Mbps) and lowest mobile multi-server latency (38 ms) during Q2 2023. In the fixed broadband market, Movistar recorded the fastest median download speed (98.37 Mbps) and lowest multi-server latency (12 ms). Among Argentina’s most populous cities, Buenos Aires recorded the fastest download speeds across mobile and fixed broadband networks.
  • Belize: Digi had the fastest median mobile download and upload speeds of 17.61 Mbps and 9.88 Mbps respectively during Q2 2023. It also recorded the highest Consistency of 79.8%. smart! recorded the lowest median mobile multi-server latency, of 67 ms. NEXGEN had the fastest median download and upload performance over fixed broadband in Belize at 48.65 Mbps and 47.38 Mbps respectively.
  • Canada: Bell was the fastest mobile operator in Canada with a median download speed of 116.59 Mbps in Q2 2023. Bell also had the fastest median 5G download speed at 208.05 Mbps. Rogers had the fastest median mobile upload speed of 13.29 Mbps, and the highest Consistency of 84.7%. Bell pure fibre was fastest for fixed broadband across both download (277.24 Mbps) and upload (235.27 Mbps) speeds. Of Canada’s most populous cities, St. John’s recorded the fastest median mobile download speed (214.29 Mbps) and Fredericton recorded the fastest median fixed download speed (239.28 Mbps). 
  • Colombia: Movistar was fastest for fixed broadband with a median download speed of 161.28 Mbps in Q2 2023. ETB had the lowest median multi-server latency over fixed broadband at 8 ms. Of Colombia’s most populous cities, Cartagena recorded the fastest median fixed download speed of 109.01 Mbps.
  • Costa Rica: Claro had the fastest median download and upload speeds among mobile operators at 51.88 Mbps and 12.56 Mbps respectively. Liberty had the lowest mobile multi-server latency at 34 ms, and the highest Consistency at 79.7%. Metrocom was fastest for fixed broadband download and upload performance, at 192.00 Mbps and 143.94 Mbps respectively.
  • Dominican Republic: Claro had the fastest median download and upload speeds among mobile operators at 30.60 Mbps and 8.70 Mbps respectively. Viva had the lowest mobile multi-server latency at 44 ms. SpaceX’s Starlink was fastest for fixed broadband at 57.31 Mbps.
  • Ecuador: CNT was the fastest mobile operator in Ecuador with a median download speed of 28.45 Mbps in Q2 2023. It also recorded the highest Consistency of 81.5%. Movistar registered the lowest median multi-server latency in Ecuador at 39 ms. Netlife was fastest for fixed broadband, at 78.36 Mbps.
  • El Salvador: Claro had the fastest median download and upload speeds among mobile operators at 42.00 Mbps and 15.42 Mbps respectively. Movistar registered the lowest median multi-server latency in El Salvador at 65 ms. Cable Color recorded the fastest median fixed download speed (51.14 Mbps), upload speed (47.58 Mbps), and lowest median multi-server latency (35 ms).
  • Guatemala: Claro was the fastest mobile operator in Guatemala with a median download speed of 34.67 Mbps and median upload speed of 20.68 Mbps. Claro also had the highest Consistency with 84.4% of results showing at least a 5 Mbps minimum download speed and 1 Mbps minimum upload speed. Claro was also fastest for median fixed download performance, at 40.60 Mbps, while Cable Color was fastest for fixed upload performance, at 26.85 Mbps, and had the lowest median multi-server latency, of 35 ms.
  • Guyana: ENet was the top performing operator in the market, recording a median mobile download and upload speed of 67.58 Mbps and 20.92 Mbps respectively, and a median fixed download and upload speed of 62.40 Mbps and 39.66 Mbps respectively, in Q2 2023. ENet also recorded the lowest median multi-server latency across mobile and fixed networks.
  • Haiti: Digicel was the fastest mobile operator in Haiti with a median mobile download speed of 10.53 Mbps and median upload speed of 6.99 Mbps. SpaceX Starlink had the fastest median fixed download speed at 60.24 Mbps, while Natcom had the fastest median fixed upload speeds (17.76 Mbps) and lowest median fixed multi-server latency at 32 ms. 
  • Jamaica: Flow was the fastest mobile operator in Jamaica with a median download speed of 35.56 Mbps. Flow also had the lowest mobile median multi-server latency at 36 ms. SpaceX Starlink had the fastest median fixed speeds at 84.93 Mbps.
  • Mexico: Telcel had the fastest median download speed over mobile at 48.76 Mbps, and for 5G at 223.93 Mbps. Telcel also had the lowest mobile median multi-server latency at 64 ms. Totalplay was fastest for fixed broadband (87.03 Mbps) and had the lowest median multi-server latency at 24 ms. Among Mexico’s most populous cities, Guadalajara recorded the fastest median mobile download speed of 39.13 Mbps, and Monterrey the fastest median fixed download speed of 78.30 Mbps.
  • Peru: Claro was the fastest mobile operator with a median download speed of 22.67 Mbps, and had the highest mobile network Consistency in the market with 80.4%. Apple devices had the fastest median download speed among top device manufacturers at 29.68 Mbps.
  • Trinidad and Tobago: Digicel had the fastest median download speed over mobile at 37.34 Mbps, and highest Consistency of 87.7%. Digicel+ had the fastest median fixed broadband download and upload speed at 99.11 Mbps and 98.32 Mbps respectively, and the lowest median multi-server latency at 7 ms.
  • United States: T-Mobile was the fastest mobile operator with a median download speed of 164.76 Mbps. T-Mobile also had the fastest median 5G download speed at 220.00 Mbps, and lowest 5G multi-server latency of 51 ms. Spectrum edged out Cox as the fastest fixed broadband provider with a median download speed of 243.02 Mbps. Verizon had the lowest median multi-server latency on fixed broadband at 15 ms.
  • Venezuela: Digitel was the fastest mobile operator with a median download speed of 9.53 Mbps, and had the highest mobile network Consistency in the market with 58.1%. Airtek Solutions had the fastest fixed median download speed of 73.44 Mbps, and lowest median multi-server latency at 8 ms.

Asia

  • Afghanistan: The fastest mobile operator in Afghanistan was Afghan Wireless with a median download speed of 7.17 Mbps. It also had the lowest median multi-server latency at 78 ms, and highest Consistency of 58.1% in Q2 2023.
  • Bangladesh: Banglalink was the fastest mobile operator in Bangladesh with a median download speed of 23.47 Mbps in Q2 2023. DOT Internet was the fastest fixed broadband provider with a median download speed of 90.88 Mbps and had the lowest median multi-server latency at 4 ms.
  • Bhutan: There was no fastest mobile operator in Bhutan during Q2 2023, but TashiCell had the lowest median multi-server latency at 42 ms, and offered the highest Consistency in the market with 83.8%.
  • Brunei: There was no statistical winner for fastest mobile download performance during Q2 2023 in Brunei, but Apple devices had the fastest median download speed at 143.97 Mbps.
  • Cambodia: Cellcard recorded the fastest median mobile download speeds at 31.60 Mbps during Q2 2023. SINET had the fastest median fixed download speed at 42.26 Mbps.
  • China: China Mobile was the fastest mobile operator with a median download speed of 132.81 Mbps. China Mobile also had the fastest median mobile 5G download speed at 279.14 Mbps. China Unicom was fastest for fixed broadband at 222.22 Mbps.
  • Georgia: There was no statistical winner for fastest mobile download performance during Q2 2023 in Georgia. Geocell recorded the lowest median mobile multi-server latency at 39 ms, while Magti recorded the highest mobile Consistency with 90.0%. MagtiCom had the fastest median fixed speed at 27.81 Mbps. MagtiCom also had the lowest median multi-server latency at 11 ms.
  • Indonesia: Telkomsel was the fastest Indonesian mobile operator with a median download speed of 28.71 Mbps. Telkomsel also had the lowest median mobile multi-server latency at 46 ms.
  • Japan: There was no statistical winner for fastest mobile download performance during Q2 2023 in Japan, however Rakuten recorded the fastest mobile upload speed at 19.90 Mbps. So-net had the fastest fixed download and upload speeds, at 276.58 Mbps and 179.51 Mbps respectively, and the lowest median multi-server latency at 9 ms.
  • Malaysia: TIME was the fastest fixed provider in Malaysia with a median download speed of 108.38 Mbps, and had the lowest multi-server latency at 9 ms.
  • Pakistan: Transworld had the fastest median fixed broadband download speed in Pakistan at 17.10 Mbps, and the highest Consistency, at 36.6%.
  • Philippines: Smart delivered the fastest median mobile download speed in the Philippines at 35.39 Mbps. 
  • South Korea: SK Telecom recorded the fastest median mobile download and upload speeds at 161.16 Mbps and 16.37 Mbps respectively. LG U+ had the lowest median multi-server latency in the market at 63 ms. KT delivered the fastest median fixed download speed at 131.09 Mbps.
  • Sri Lanka: SLT-Mobitel delivered the fastest mobile and fixed broadband speeds in Sri Lanka at 20.71 Mbps and 38.97 Mbps, respectively in Q2 2023. Dialog had the lowest median mobile multi-server latency at 35 ms, and the highest Consistency, at 81.8%.
  • United Arab Emirates: etisalat by e& recorded the fastest median download speeds across both mobile and fixed, at 216.65 Mbps and 261.98 Mbps respectively in Q2 2023. etisalat by e& also had the fastest median 5G download speed at 680.88 Mbps and lowest median mobile multi-server latency at 35 ms. du recorded the lowest fixed multi-server latency, at 12 ms.
  • Vietnam: Vinaphone had the fastest median mobile download speed in Q2 2023, at 52.58 Mbps. It also had the lowest median mobile multi-server latency at 34 ms, and highest Consistency at 94.8%. Viettel was the fastest fixed provider with a median download speed of 105.72 Mbps.

Europe

  • Albania: Digicom was the fastest fixed broadband provider in Albania in Q2 2023, recording a median download speed of 93.40 Mbps. It also recorded the highest Consistency in the market, at 86.0%. There was no winner for fastest mobile operator in the market.
  • Belgium: Proximus recorded the fastest median mobile download speed during Q2 2023, at 78.01 Mbps. It also recorded the highest Consistency in the market, at 90.5%. Telenet had the fastest median fixed download speed at 143.42 Mbps. Among Belgium’s most populous cities, Ghent recorded the fastest median mobile download speed of 187.90 Mbps, and Antwerp the fastest median fixed download speed of 87.72 Mbps.
  • Denmark: YouSee was the fastest mobile operator in Denmark with a median download speed of 140.59 Mbps. Hiper was fastest for fixed broadband at 268.02 Mbps.
  • Estonia: The fastest mobile operator in Estonia was Telia with a median download speed of 101.32 Mbps. Telia also had the lowest median multi-server latency on mobile at 31 ms. Elisa was the fastest fixed broadband provider, with a median download speed of 94.70 Mbps.
  • Finland: DNA had the fastest median mobile download speed at 99.07 Mbps. Lounea was fastest for fixed broadband at 105.84 Mbps and had the lowest median multi-server latency at 11 ms.
  • Germany: Telekom was the fastest mobile operator in Germany with a median download speed of 93.39 Mbps, and a median download speed with 5G at 187.25 Mbps. Vodafone recorded the fastest fixed broadband performance, with a median download speed at 121.76 Mbps. It also recorded the highest Consistency in the market, at 83.8%.
  • Latvia: BITĖ was the fastest mobile operator in Latvia during Q2 2023, with a median download speed of 114.51 Mbps. LMT recorded the lowest mobile multi-server latency, at 26 ms.  Balticom was fastest for fixed broadband with a median download speed of 243.92 Mbps. Balticom also had the lowest median fixed broadband multi-server latency at 4 ms.
  • Lithuania: The mobile operator with the fastest median download speed was Telia at 117.68 Mbps in Q2 2023. It also recorded the highest Consistency in the market, at 95.0%. Cgates was fastest for fixed broadband with a median download speed at 161.67 Mbps.
  • Poland: UPC was the fastest provider for fixed broadband with a median download speed of 223.32 Mbps in Q2 2023. There was no statistical winner for fastest mobile operator during Q2 2023, however Plus recorded the fastest median 5G download performance, at 153.19 Mbps.
  • Switzerland: Salt blazed ahead for the fastest fixed broadband in Switzerland, with a median download speed of 358.73 Mbps. Salt also had the lowest median multi-server latency over fixed broadband at 8 ms, and highest Consistency in the market, at 94.1%.
  • Turkey: Turkcell was the fastest mobile operator in Turkey with a median download speed of 58.52 Mbps. Türk Telekom had the lowest median mobile multi-server latency at 39 ms. TurkNet was fastest for fixed broadband, with a median download speed of 62.80 Mbps. It recorded the lowest median fixed multi-server latency, at 13 ms, and highest Consistency, at 80.5%. Among Turkey’s most populous cities, Istanbul recorded the fastest median download speeds across mobile and fixed, of 39.89 Mbps, and 40.27 Mbps respectively.

Oceania

  • New Zealand: Speedtest Intelligence data showed no winner for fastest mobile operator in New Zealand during Q2 2023. 2degrees had the lowest median mobile multi-server latency at 40 ms, and the highest Consistency, at 91.6%.

The Speedtest Global Index is your resource to understand how internet connectivity compares around the world and how it’s changing. Check back next month for updated data on country and city rankings, and look for updated Ookla Market Reports with Q3 2023 data in October.

Ookla retains ownership of this article including all of the intellectual property rights, data, content graphs and analysis. This article may not be quoted, reproduced, distributed or published for any commercial purpose without prior consent. Members of the press and others using the findings in this article for non-commercial purposes are welcome to publicly share and link to report information with attribution to Ookla.

| June 27, 2017

Which Airport Has the Fastest Internet in Asia?

Travelers jetting off to Asia this summer will probably want to know whether you can connect to the internet upon landing and whether that internet is fast enough to help you nail down any final travel details before hitting the hotel and sleeping off the jet lag.

Using Speedtest data for March-May 2017, we analyzed the speeds of free airport Wi-Fi and local cellular signals at the busiest airports in Asia to see what your best options are and where you’re flat out of luck.

Fastest airport Wi-Fi

Dubai reigns when it comes to free airport Wi-Fi. In fact, this airport has the fastest Wi-Fi we’ve seen at any airport in Asia, Europe or Africa. And their average upload speed is even faster than their download. Travelers to second-place Seoul are also in excellent shape if they need to connect to the internet while in transit.

Tokyo, Delhi and Singapore have decently fast download speeds over airport Wi-Fi while Bangkok’s and Hong Kong’s are merely okay. Sadly, the rest of the airports offer painfully slow free Wi-Fi.

You might think airport Wi-Fi is similar to the average mobile Wi-Fi speeds of the country, but instead some of the fastest countries — Singapore (111.59 Mbps), Hong Kong (63.70 Mbps) and China (47.64 Mbps) — have poor to average airport Wi-Fi speeds. Though sitting near the top of the airport Wi-Fi pack, South Korea’s 66.67 Mbps, Japan’s 42.00 Mbps and Thailand’s 30.48 Mbps country averages show the Wi-Fi at their premier airports could be a lot faster. India’s average download speed (12.39 Mbps) is right in line with the Wi-Fi at Indira Gandhi International Airport.

On the other end of the spectrum, the United Arab Emirates has clearly prioritized airport Wi-Fi because the Wi-Fi download speed at Dubai International is nearly double the country average of 22.12 Mbps.

Fastest airport cell

In countries including China and India, you can’t connect to the free airport Wi-Fi without an in-country mobile number, so we checked Speedtest results for users on cell networks as well.

The average mobile download speed at Singapore’s Changi Airport is nearly as fast as the country’s average of 46.12 Mbps. Considering Singapore ranks second fastest in the world for mobile downloads, that’s a hard speed to beat. Dubai also has wonderfully fast speeds, and they beat the country average of 29.81 Mbps.

East Asia’s airports form a strong middle of the pack with cellular download speeds ranging from 18.18 Mbps in Bangkok to 27.12 in Guangzhou. These are comparable to the country average mobile download speeds of 33.63 Mbps for China, 19.70 Mbps for Hong Kong, 18.48 for Japan, and 14.58 for Thailand. Flyers at Delhi’s Indira Gandhi Airport, though, will be sorely disappointed with the 5.85 Mbps on offer. But that’s only slightly slower than India’s 7.62 Mbps mobile download average.

Wi-Fi or cell?

If you’ve already nailed down your international SIM card options, you’re going to have a lot better luck in many parts of Asia on a cellular signal than you would using the free airport Wi-Fi.

Of course you’re in good shape either way in Dubai, Seoul’s Wi-Fi download speed is slightly faster than that on cell, and in India you’ll definitely want to use the airport Wi-Fi if you can access it. Everywhere else the local cell performance puts airport Wi-Fi to shame.

Regional trends

Southeast Asia

If you’re jet-setting through Southeast Asia, count on any time spent in the Singapore Airport for your internet needs and plan to enjoy a more disconnected experience in India and Thailand, especially if you don’t have an Indian phone number and have to rely on cell service at the Delhi airport.

East Asia

As mentioned above, all the airports we analyzed in China, Japan and Korea had strong cellular speeds. Tokyo’s Haneda Airport and Seoul’s Incheon Airport also had good download speeds over their free airport Wi-Fi networks. China’s free airport Wi-Fi, on the other hand, is varying degrees of slow.

China

Within China, Hong Kong has the fastest free airport Wi-Fi, but you will be much better off with cellular networks at any of the airports we surveyed in China. Guangzhou has the fastest average download on cell while Hong Kong is the slowest, but with averages between 22 Mbps and 28 Mbps, you should be just fine.

Watch this space for upcoming articles comparing Wi-Fi and cellular speeds at airports across the globe. Until then, if you think your local airport is over- (or under-) rated, take a Speedtest on Android or iOS and show us what you’re experiencing.

Ookla retains ownership of this article including all of the intellectual property rights, data, content graphs and analysis. This article may not be quoted, reproduced, distributed or published for any commercial purpose without prior consent. Members of the press and others using the findings in this article for non-commercial purposes are welcome to publicly share and link to report information with attribution to Ookla.

| January 24, 2018

GOOOOAL: Which World Cup Finalist Scored the Fastest Internet in their Capital City?

Whether you call it soccer or football, everyone calls the World Cup fun. We couldn’t wait for the actual match-ups in June, so we decided to pit the qualifying countries against one another to see who has the fastest internet speeds in their capital cities. The results might surprise you.

Get ready to watch Russia best Brazil and Portugal defeat Iran; meanwhile, Argentina and Nigeria and Belgium and England are preparing for penalty shoot-outs.

Using data from Speedtest Intelligence for Q3-Q4 2017, we’ve calculated which capital cities of World Cup-qualifying countries have the fastest mobile and fixed broadband speeds. We also took a peek at the fastest carriers and internet service providers (ISPs) in each capital using Speed Score, a comprehensive metric that combines measures of internet performance at all levels.

Mobile winners

Iceland’s sixth place ranking for mobile download speed in the Speedtest Global IndexTM virtually assured that Reykjavík would come out at the top of the list of fastest World Cup contenders. Canberra represents Australia well with a second place finish for mobile download speeds among World Cup capitals. And Brussels, Belgium barely surpasses Bern, Switzerland for a third place finish.

Mobile Internet Speeds
Capitals of World Cup Qualifying Countries | Q3 – Q4 2017
Country Capital City Average Download (Mbps) Average Upload (Mbps)
Iceland Reykjavík 55.49 21.53
Australia Canberra 44.24 12.60
Belgium Brussels 42.52 16.74
Switzerland Bern 42.02 17.52
South Korea Seoul 41.85 14.15
Denmark Copenhagen 41.78 18.29
Croatia Zagreb 41.16 16.40
Sweden Stockholm 40.12 12.63
Spain Madrid 38.30 14.02
Portugal Lisbon 30.60 11.39
Serbia Belgrade 30.33 12.49
France Paris 29.03 9.26
Poland Warsaw 26.94 9.84
Germany Berlin 25.83 9.51
England London 25.09 11.49
Russia Moscow 21.89 8.49
Japan Tokyo 19.89 7.10
Uruguay Montevideo 19.82 11.49
Mexico Mexico City 19.11 11.51
Peru Lima 18.33 12.90
Tunisia Tunis 18.27 8.07
Brazil Brasília 18.00 8.64
Morocco Rabat 17.32 9.76
Colombia Bogotá 16.87 9.50
Nigeria Abuja 16.17 6.76
Iran Tehran 15.05 7.04
Argentina Buenos Aires 13.77 7.70
Egypt Cairo 13.15 6.33
Panama Panama City 12.89 8.45
Saudi Arabia Riyadh 12.28 8.88
Senegal Dakar 8.85 3.81
Costa Rica San José 5.97 3.33

Looking at the group draw, Group A fares the worst with 16th place Moscow, Russia being the capital city with the fastest mobile downloads in the group. In Group B, Spain comes out on top. Australia wins Group C, Iceland takes Group D, Switzerland leads Group E and South Korea has the fastest mobile download speed in Group F. Belgium finishes first in Group G and Poland prevails in Group H, despite a 13th place finish overall.

From a regional perspective, European capitals top the rankings with all 14 European World Cup capitals sitting in the top half of the list. Latin American, Middle Eastern and African cities fare worst. Asia’s two contenders are split with Seoul boasting the fifth fastest mobile download speed among World Cup capitals and Tokyo, Japan coming in 17th.

The fastest World Cup capital in Latin America (Montevideo, Uruguay) shows a 64.3% slower mobile download speed than Reykjavík. First place among African World Cup capitals, Rabat, Morocco is 68.8% slower than Reykjavík for mobile downloads. And Tehran, Iran, the fastest World Cup capital in the Middle East, is 72.9% slower than Reykjavík.

Fastest carriers

We also looked into which carriers were fastest in each of the 32 World Cup capital cities.

With Speed Scores ranging from 8.89 in Dakar, Senegal to 46.57 in Brussels, mobile carrier Orange was fastest in four cities and tied for fastest in one. Vodafone was fastest in both Lisbon, Portugal and Madrid, Spain with comparable Speed Scores in the two locations. The rest of the cities show the diversity of fastest carriers that you might expect from a worldwide competition.

Fastest Carriers Speeds
Capitals of World Cup Qualifying Countries | Q3 – Q4 2017
Country Capital City Fastest Carrier Speed Score
Argentina Buenos Aires Personal 16.15
Australia Canberra Telstra 50.21
Belgium Brussels Orange 46.57
Brazil Brasília Claro 24.72
Colombia Bogotá Avantel 20.93
Costa Rica San José ICE 8.30
Croatia Zagreb Hrvatski Telekom 49.35
Denmark Copenhagen TDC / Telia 45.34 / 45.09
Egypt Cairo Orange 16.50
England London EE 36.83
France Paris Orange 33.15
Germany Berlin Telekom 53.54
Iceland Reykjavík Nova 64.61
Iran Tehran MTN IranCell 15.89
Japan Tokyo SoftBank 27.26
Mexico Mexico City AT&T 20.26
Morocco Rabat inwi 20.51
Nigeria Abuja MTN 29.23
Panama Panama City Cable & Wireless Panama / Movistar 14.85 / 14.80
Peru Lima Entel Peru 20.73
Poland Warsaw T-Mobile 36.07
Portugal Lisbon Vodafone 42.44
Russia Moscow MegaFon 37.06
Saudi Arabia Riyadh Zain 13.20
Senegal Dakar Orange 8.89
Serbia Belgrade Vip mobile 45.56
South Korea Seoul LG U+ 50.03
Spain Madrid Vodafone 40.17
Sweden Stockholm Telia 54.49
Switzerland Bern Sunrise / Swisscom 42.14 / 41.91
Tunisia Tunis Ooredoo / Orange 19.90 / 19.89
Uruguay Montevideo Antel 20.35

Fixed broadband winners

Given that Iceland ranks second in the world for fixed broadband download speed on the Speedtest Global Index and has the world’s highest gigabit user penetration (GUP), we’re not surprised to see Reykjavík shut out the competition by coming out on top of World Cup contenders for fixed broadband speed, too. Seoul, South Korea comes in second for fixed broadband download speed among World Cup capitals and Paris, France takes third.

Fixed Broadband Internet Speeds
Capitals of World Cup Qualifying Countries | Q3 – Q4 2017
Country Capital City Average Download (Mbps) Average Upload (Mbps)
Iceland Reykjavík 142.89 154.28
South Korea Seoul 130.75 131.96
France Paris 112.58 55.86
Sweden Stockholm 98.77 66.68
Spain Madrid 86.59 73.43
Japan Tokyo 75.88 70.46
Denmark Copenhagen 72.74 52.13
Switzerland Bern 68.82 54.44
Poland Warsaw 62.57 16.19
Portugal Lisbon 55.80 30.97
England London 52.53 16.12
Germany Berlin 46.84 9.52
Russia Moscow 45.25 42.96
Belgium Brussels 43.25 9.63
Panama Panama City 29.11 5.93
Australia Canberra 28.85 12.46
Serbia Belgrade 26.45 5.59
Croatia Zagreb 26.20 11.40
Mexico Mexico City 24.11 10.14
Uruguay Montevideo 23.02 5.82
Argentina Buenos Aires 22.03 4.26
Brazil Brasília 21.57 5.29
Saudi Arabia Riyadh 20.93 9.05
Peru Lima 18.15 3.51
Colombia Bogotá 13.43 6.48
Morocco Rabat 11.83 2.51
Iran Tehran 9.33 4.18
Costa Rica San José 8.79 4.29
Nigeria Abuja 8.07 5.27
Tunisia Tunis 7.82 4.49
Senegal Dakar 7.42 3.11
Egypt Cairo 5.61 1.92

Group A again suffers on the fixed side with leader Russia coming in 13th based on Moscow’s fixed broadband download speed. Spain’s still the front-runner of Group B. France takes Group C, Iceland wins Group D, Switzerland tops Group E, South Korea reigns over Group F, England heads up Group G and Japan starts Group H based on average download speeds over fixed broadband in their respective capitals.

European capitals again fare well, with 12 of the 14 placing in the top half of fastest World Cup capitals for fixed broadband download speed. Belgrade, Serbia and Zagreb, Croatia rank 17th and 18th, respectively. Tokyo ranks much better for fixed broadband download speed than for mobile, which puts both Asian World Cup capitals in the top six.

With the exception of Panama City, Panama, which ranks 15th, all Latin American World Cup capitals are in the bottom half of the list for download speed over fixed broadband. As are all Middle Eastern and African capital cities.

Panama City’s fixed broadband download speed is 79.6% slower than Reykjavík’s. Riyadh, Saudia Arabia boasts the title of fastest World Cup capital in the Middle East, but is still 85.4% slower for fixed broadband downloads than Reykjavík. The fastest World Cup capital in Africa — Rabat, Morocco — is 91.7% slower than Reykjavík.

Fastest providers

Comparing Speed Scores for fixed broadband across World Cup capitals, Vodafone had wins in Berlin, Germany and Lisbon and Orange took Paris and tied for first in Madrid. The rest of the fastest ISPs vary by location as listed below:

Fastest ISPs Speeds
Capitals of World Cup Qualifying Countries | Q3 – Q4 2017
Country Capital City Fastest ISP Speed Score
Argentina Buenos Aires Cablevisión Fibertel 21.72
Australia Canberra iiNet 33.23
Belgium Brussels Telenet 66.95
Brazil Brasília NET Virtua 27.30
Colombia Bogotá ETB 19.17
Costa Rica San José Cabletica 8.28
Croatia Zagreb vip 30.23
Denmark Copenhagen Fiberby 103.26
Egypt Cairo TE Data 4.84
England London Hyperoptic 117.40
France Paris Orange 107.20
Germany Berlin Vodafone 55.46
Iceland Reykjavík Nova 278.06
Iran Tehran Mobin Net 11.74
Japan Tokyo So-net 118.05
Mexico Mexico City Axtel 45.83
Morocco Rabat Maroc Telecom 9.25
Nigeria Abuja MTN 10.73
Panama Panama City Cable Onda 25.08
Peru Lima Movistar 16.64
Poland Warsaw UPC 82.72
Portugal Lisbon Vodafone 61.80
Russia Moscow MGTS 62.00
Saudi Arabia Riyadh STC 16.46
Senegal Dakar Tigo 6.42
Serbia Belgrade SBB 34.60
South Korea Seoul KT 162.45
Spain Madrid Masmovil / Orange 101.52 / 101.34
Sweden Stockholm Ownit 158.78
Switzerland Bern Fiber7 241.93
Tunisia Tunis TOPNET 7.61
Uruguay Montevideo Antel 22.01

Did your team not come out as expected? Or are you defending a tight match? Take a Speedtest on Android, iOS or on the web and we’ll check back in on scores closer to the main event.

Ookla retains ownership of this article including all of the intellectual property rights, data, content graphs and analysis. This article may not be quoted, reproduced, distributed or published for any commercial purpose without prior consent. Members of the press and others using the findings in this article for non-commercial purposes are welcome to publicly share and link to report information with attribution to Ookla.

| May 2, 2018

The American Globetrotter's Guide to Roaming Speeds

Mobile roaming has come a long way from the days when I spent most of my tour of China touring hotel lobbies desperately hoping to connect my U.S. flip phone to the Wi-Fi. Not only can you actually get a signal in most countries these days, some carriers offer special packages for the jet set so you don’t have to pay extra for roaming calls and data.

But how are the speeds?

Using Q1 2018 Speedtest® data, we’re here to report on mobile roaming speeds for U.S. consumers in 15 popular destinations, including which carriers are fastest where. For overall speeds we look at data from all devices and when we analyze carriers we look only at data for modern (LTE-capable) devices.

Where roaming speeds will (and will not) let you down

Get thee to Canada! Our analysis of roaming Speedtest results found that U.S. customers in Canada saw a mean download speed of 42.03 Mbps during Q1 2018. That’s not quite as fast as the 45.28 Mbps Canadians receive on their home mobile networks, but it beats the 27.08 Mbps average in the U.S.

Roaming Speeds for U.S. Customers Abroad
Q1 2018
Country Download (Mbps) Upload (Mbps)
Canada 42.03 13.50
South Korea 21.81 8.60
Mexico 18.02 10.18
Spain 13.23 7.09
Italy 12.70 6.38
France 12.48 5.45
Australia 11.84 6.96
Japan 10.91 4.79
United Kingdom 10.40 5.68
Germany 9.02 4.03
Costa Rica 7.72 4.11
China 7.05 3.91
Dominican Republic 5.75 3.58
India 2.96 1.96
The Bahamas 1.70 2.99

Second place South Korea showed roaming speeds for U.S. travelers about half as fast as those in Canada. Mexico was third fastest. The middle tier of the roaming speed ranking is taken up mostly by western European countries (with Japan and Australia to break up the pack).

At the bottom of the spectrum, Bahamian roaming speeds are painfully slow. They aren’t much better in India or the Dominican Republic.

A lot of factors go into the roaming speeds you’ll experience abroad, including how carriers prioritize out of country traffic, something that’s decided between each individual carrier in each individual country.

How does your carrier stack up?

Your roaming experience on your next trip is going to depend a lot on which carrier you have, so we broke our roaming speed analysis of Speedtest results on modern devices down to the carrier level.

US Carrier Speeds While Roaming Abroad
Q1 2018 | Mean Download (Mbps)
Country AT&T Sprint T-Mobile Verizon Wireless
Australia 21.24 N/A 2.14 22.14
Canada 26.53 27.65 53.56 43.22
China 17.23 4.77 1.15 13.15
Costa Rica 13.67 N/A 0.70 14.86
Dominican Republic 11.00 N/A 0.57 7.68
France 22.72 N/A 1.96 26.30
Germany 20.55 N/A 1.86 20.58
India 4.92 1.70 0.79 7.13
Italy 24.05 N/A 1.99 25.19
Japan 18.22 24.79 1.40 11.46
Mexico 19.95 9.66 17.22 22.35
South Korea 27.97 17.49 21.67 N/A
Spain 29.27 N/A 1.18 24.82
The Bahamas 1.79 N/A 0.25 3.53
United Kingdom 19.87 9.07 1.74 16.61

From the above, it looks like there’s no one right answer for the fastest roaming carrier. And there are other things to consider when roaming, too, like does your carrier offer a special plan that includes free roaming or are you paying through the nose.

It’s important to remember that roaming comes at a cost to carriers, which means that if your carrier includes free or low-cost roaming on almost all types of plans, the trade-off might be that you get slower speeds than you would with another carrier.

So if speed is your primary criterion, there are two standouts on this list. Verizon wins eight of the 15 countries we analyzed and AT&T wins six. T-Mobile and Sprint each win one country. We excluded Sprint from the running in eight countries because of a low number of test results.

Are you roaming (for business or pleasure) this summer? Take a Speedtest on Android or iOS to show us how fast (or slow) your connection is.

Ookla retains ownership of this article including all of the intellectual property rights, data, content graphs and analysis. This article may not be quoted, reproduced, distributed or published for any commercial purpose without prior consent. Members of the press and others using the findings in this article for non-commercial purposes are welcome to publicly share and link to report information with attribution to Ookla.