Average Price for GCP Regions
Below, you can find a chart showing the average price in USD per hour for the most common instances in each region. The calculation is based on: n1-standard-2, n2-standard-2, n2d-standard-2, c3-standard-4, e2-standard-2, t2d-standard-2, and g2-standard-4 instances. Other instance types are excluded as they are not offered in all regions. The chart displays the average prices across various regions. However, certain instances may be less expensive in regions other than the cheapest one. To find the cheapest region, visit the main page . The "Best Price Region" is indicated in the corresponding column.
The latest update occurred on April 26, 2024 at 12:02 AM UTC
Here is the map with all GCP regions https://cloud.google.com/about/locations
Geography | Location | Location | Region | Average price of Instances per hour (USD) |
|---|---|---|---|---|
| North America | Ohio | Columbus | us-east5 | 0.08328 |
| Middle East | Israel | Tel Aviv | me-west1 | 0.09418 |
| North America | Québec | Montréal | northamerica-northeast1 | 0.09426 |
| North America | Ontario | Toronto | northamerica-northeast2 | 0.09426 |
| Europe | Finland | Hamina | europe-north1 | 0.09427 |
| Europe | Italy | Milan | europe-west8 | 0.0966 |
| Europe | France | Paris | europe-west9 | 0.0966 |
| Europe | Spain | Madrid | europe-southwest1 | 0.09827 |
| North America | Texas | Dallas | us-south1 | 0.09827 |
| Middle East | Qatar | Doha | me-central1 | 0.10118 |
| APAC | India | Delhi | asia-south2 | 0.10284 |
| North America | California | Los Angeles | us-west2 | 0.10284 |
| North America | Utah | Salt Lake City | us-west3 | 0.10284 |
| Europe | Italy | Turin | europe-west12 | 0.10743 |
| Africa | South Africa | Johannesburg | africa-south1 | 0.10893 |
| APAC | Japan | Osaka | asia-northeast2 | 0.10992 |
| Europe | Poland | Warsaw | europe-central2 | 0.11031 |
| APAC | Indonesia | Jakarta | asia-southeast2 | 0.11513 |
| South America | Chile | Santiago | southamerica-west1 | 0.11909 |
| APAC | Hong Kong | Hong Kong | asia-east2 | 0.1198 |
| APAC | Australia | Sydney | australia-southeast1 | 0.12149 |
| APAC | Australia | Melbourne | australia-southeast2 | 0.12149 |
| Europe | Germany | Berlin | europe-west10 | 0.12825 |
| Middle East | Saudi Arabia | Dammam | me-central2 | 0.13325 |
| South America | Brazil | Osasco, São Paulo | southamerica-east1 | 0.13591 |
| North America | Iowa | Council Bluffs | us-central1 | 0.19196 |
| North America | South Carolina | Moncks Corner | us-east1 | 0.19196 |
| North America | Oregon | The Dalles | us-west1 | 0.19196 |
| APAC | India | Mumbai | asia-south1 | 0.19309 |
| North America | Virginia | Ashburn | us-east4 | 0.19925 |
| Europe | Netherlands | Eemshaven | europe-west4 | 0.20481 |
| Europe | Belgium | St. Ghislain | europe-west1 | 0.21128 |
| North America | Nevada | Las Vegas | us-west4 | 0.21304 |
| APAC | Taiwan | Changhua County | asia-east1 | 0.21902 |
| Europe | England | London | europe-west2 | 0.22606 |
| Europe | Germany | Frankfurt | europe-west3 | 0.23077 |
| APAC | Singapore | Jurong West | asia-southeast1 | 0.23682 |
| APAC | Japan | Tokyo | asia-northeast1 | 0.24282 |
| Europe | Switzerland | Zurich | europe-west6 | 0.26462 |
| APAC | South Korea | Seoul | asia-northeast3 | 0.26976 |