Chile Cities with Latitude & Longitude – Download in Excel, CSV, SQL, JSON, XML
Last update : 23 March 2026.
Here you’ll find a curated sample of 100 key cities from Chile, each with essential data points such as latitude, longitude, administrative region, and other relevant attributes.
This preview is extracted from our full dataset, which includes a total of 2728 geographic locations across Chile.
Whether you’re working on mapping, analytics, or app development, the data is available for both personal and commercial use.
All entries can be downloaded in five formats: Excel (.xlsx), CSV, SQL, JSON, and XML.
Capital Highlight: The official capital city of Chile is Santiago.
| Geoname_ID | City | Alternate_Name | Country_Code | Region | Sub_region | Latitude | Longitude | Elevation | Population | Timezone | Fcode_Name |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 3890338 | El Tabo | El Tabo | CL | Valparaíso | San Antonio Province | -33.45548 | -71.66683 | 0 | America/Santiago | populated place | |
| 11967420 | Paredones | Paredones | CL | Biobío | -36.93822 | -72.4422 | 0 | America/Santiago | populated place | ||
| 11897886 | Punta Falsa | Punta Falsa | CL | Los Ríos Region | -39.96697 | -73.66703 | 0 | America/Santiago | populated place | ||
| 12440898 | Carrizalillo | Carrizalillo | CL | Atacama | -27.66672 | -69.79467 | 0 | America/Santiago | populated place | ||
| 11954719 | La Suerte | La Suerte | CL | Biobío | -37.55094 | -72.55734 | 0 | America/Santiago | populated place | ||
| 11954858 | Sara de Lebu | Sara de Lebu | CL | Biobío | -37.75868 | -73.48333 | 0 | America/Santiago | populated place | ||
| 12469594 | Punta Durazno | Punta Durazno | CL | Santiago Metropolitan | -33.82373 | -70.86023 | 0 | America/Santiago | populated place | ||
| 12013309 | La Cabaña | La Cabana,La Cabaña | CL | O’Higgins Region | -34.66278 | -71.83588 | 0 | America/Santiago | populated place | ||
| 11950049 | Chacayal | Chacayal | CL | Biobío | -37.01414 | -72.67181 | 0 | America/Santiago | populated place | ||
| 11966988 | Cerrillos | Cerrillos | CL | Biobío | -36.89861 | -72.85546 | 0 | America/Santiago | populated place | ||
| 12013536 | Santa Adela Sur | Santa Adela Sur | CL | Maule Region | -34.88429 | -71.15179 | 0 | America/Santiago | populated place | ||
| 12013432 | Tres Caminos | Tres Caminos | CL | O’Higgins Region | -34.69338 | -71.76984 | 0 | America/Santiago | populated place | ||
| 11897853 | La Montaña | La Montana,La Montaña | CL | Los Ríos Region | -39.81215 | -72.30794 | 0 | America/Santiago | populated place | ||
| 11956038 | Esperanza | Esperanza | CL | Araucanía | -37.84514 | -72.39411 | 0 | America/Santiago | populated place | ||
| 3874815 | Punitaqui | Punitaqui | CL | Coquimbo Region | Provincia de Limarí | -30.83448 | -71.2586 | 0 | America/Santiago | populated place | |
| 11897818 | Puyumén | Puyumen,Puyumén | CL | Los Ríos Region | -39.68078 | -72.27863 | 0 | America/Santiago | populated place | ||
| 3892934 | Curacaví | Curacavi,Curacaví,Kurakavi,ku la ka wei,kulakabi,kywrakafay,kywrakafay shyly,Куракави,كيوراكافاي,کیوراکافای، شیلی,庫拉卡維,쿠라카비 | CL | Santiago Metropolitan | Provincia de Melipilla | -33.39762 | -71.12708 | 0 | America/Santiago | populated place | |
| 11897812 | Los Tayos | Los Tayos | CL | Los Ríos Region | -39.67305 | -72.51086 | 0 | America/Santiago | populated place | ||
| 3890405 | El Sauce | El Sauce | CL | O’Higgins Region | -34.82502 | -71.00339 | 0 | America/Santiago | populated place | ||
| 3949120 | Tulapiña | CL | Tarapacá | -17.58278 | -69.71778 | 0 | America/Lima | populated place | |||
| 3875210 | Arturo Prat | Arturo Prat,Prat | CL | O’Higgins Region | -34.07041 | -71.78612 | 0 | America/Santiago | populated place | ||
| 3872205 | San Francisco de Mostazal | San Francisco de Mostazal | CL | O’Higgins Region | Provincia de Cachapoal | -33.98219 | -70.7104 | 0 | America/Santiago | populated place | |
| 12013449 | La Matanza | La Matanza | CL | O’Higgins Region | -34.70883 | -71.05627 | 0 | America/Santiago | populated place | ||
| 11964685 | La Ciudad | La Ciudad | CL | Maule Region | -36.08865 | -72.12589 | 0 | America/Santiago | populated place | ||
| 12525007 | Los Puquios | Los Puquios | CL | Biobío | -36.89868 | -71.98844 | 0 | America/Santiago | populated place | ||
| 3882653 | Lolol | Lolol | CL | O’Higgins Region | Provincia de Colchagua | -34.73703 | -71.6107 | 0 | America/Santiago | populated place | |
| 11954412 | Planchada | Planchada | CL | Biobío | -37.22281 | -72.71439 | 0 | America/Santiago | populated place | ||
| 12012634 | Barrancas | Barrancas | CL | O’Higgins Region | -34.49628 | -71.98149 | 0 | America/Santiago | populated place | ||
| 11959225 | Las Camelias | Las Camelias | CL | Biobío | -36.72592 | -71.98257 | 0 | America/Santiago | populated place | ||
| 11897864 | Rincón de la Piedra | Rincon de la Piedra,Rincón de la Piedra | CL | Los Ríos Region | -39.91865 | -73.10813 | 0 | America/Santiago | populated place | ||
| 11897685 | Colonia Quitaqui | Colonia Quitaqui | CL | Los Ríos Region | -39.68225 | -73.26417 | 0 | America/Santiago | populated place | ||
| 11954430 | El Guape | El Guape | CL | Biobío | -37.31129 | -73.56195 | 0 | America/Santiago | populated place | ||
| 12100985 | Lago Vargas | Lago Vargas | CL | Aysén | -47.68621 | -73.05456 | 0 | America/Santiago | populated place | ||
| 12524972 | Arboleda Grande | Arboleda Grande | CL | Coquimbo Region | -31.73768 | -70.94824 | 0 | America/Santiago | populated place | ||
| 11946001 | Cahuinpangue | Cahuinpangue | CL | Araucanía | -38.94578 | -72.36949 | 0 | America/Santiago | populated place | ||
| 11917262 | Reducción Curiche | Reduccion Curiche,Reducción Curiche | CL | Araucanía | -38.39625 | -72.19431 | 0 | America/Santiago | populated place | ||
| 11954802 | Loma del Toro | Loma del Toro | CL | Araucanía | -37.63635 | -72.94786 | 0 | America/Santiago | populated place | ||
| 12004346 | El Sauce | El Sauce | CL | Maule Region | -35.62967 | -72.49042 | 0 | America/Santiago | populated place | ||
| 12524989 | Quiñenahuín | Quinenahuin,Quiñenahuín | CL | Araucanía | -39.2633 | -71.43444 | 0 | America/Santiago | populated place | ||
| 11917485 | Los Copihues | Los Copihues | CL | Araucanía | -38.53244 | -72.04649 | 0 | America/Santiago | populated place | ||
| 11967829 | Santa Amalia | Santa Amalia | CL | Maule Region | -35.04979 | -71.26581 | 0 | America/Santiago | populated place | ||
| 11900397 | El Volcán | El Volcan,El Volcán | CL | Araucanía | -39.34406 | -71.97115 | 0 | America/Santiago | populated place | ||
| 11955933 | San Luis de Malvén | San Luis de Malven,San Luis de Malvén | CL | Biobío | -37.6555 | -72.40775 | 0 | America/Santiago | populated place | ||
| 11965859 | Belén Chico | Belen Chico,Belén Chico | CL | Biobío | -36.22479 | -72.04201 | 0 | America/Santiago | populated place | ||
| 3869381 | Traiguén | Traiguen,Traiguén,Trajgen,te lai gen,teulaigen,Трайген,特賴根,트라이겐 | CL | Araucanía | Provincia de Malleco | -38.2496 | -72.67027 | 14481 | America/Santiago | populated place | |
| 11981968 | Macarena | Macarena | CL | O’Higgins Region | -34.67434 | -70.95209 | 0 | America/Santiago | populated place | ||
| 11949981 | Las Nieves | Las Nieves | CL | Biobío | -37.92135 | -72.10056 | 0 | America/Santiago | populated place | ||
| 12525000 | Monterrey | Monterrey | CL | Biobío | -37.3147 | -72.71774 | 0 | America/Santiago | populated place | ||
| 11959204 | Palma | Palma | CL | Biobío | -36.62342 | -71.86763 | 0 | America/Santiago | populated place | ||
| 3892892 | Curanilahue | Curanilahue,Kuranilaueh,Kuranilave,ku la ni la wei,kulanillaue,kywranay lahyw,kywranaylahyw shyly,Куранилаве,Куранилауэ,كيوراناي لاهيو,کیورانایلاهیو، شیلی,庫拉尼拉韋,쿠라닐라우에 | CL | Biobío | Provincia de Arauco | -37.47793 | -73.34495 | 30611 | America/Santiago | populated place | |
| 11956935 | Huenutil de la Cabrería | Huenutil de la Cabreria,Huenutil de la Cabrería | CL | Biobío | -36.31736 | -71.81118 | 0 | America/Santiago | populated place | ||
| 11961102 | La Invernada de Trentén | La Invernada de Trenten,La Invernada de Trentén | CL | Maule Region | -35.41017 | -71.36503 | 0 | America/Santiago | populated place | ||
| 11953863 | Cambrales | Cambrales | CL | Biobío | -37.05161 | -72.53175 | 0 | America/Santiago | populated place | ||
| 11954727 | Santa Fé | Santa Fe,Santa Fé | CL | Biobío | -37.60984 | -73.66893 | 0 | America/Santiago | populated place | ||
| 11897468 | Rucañuelo | Rucanuelo,Rucañuelo | CL | Los Ríos Region | -39.48361 | -72.68367 | 0 | America/Santiago | populated place | ||
| 11964710 | San Clemente | San Clemente | CL | Maule Region | -36.19645 | -72.13127 | 0 | America/Santiago | populated place | ||
| 11965974 | Bidico | Bidico | CL | Biobío | -36.47124 | -72.21085 | 0 | America/Santiago | populated place | ||
| 11982130 | La Estrella | La Estrella | CL | Maule Region | -34.87276 | -70.95835 | 0 | America/Santiago | populated place | ||
| 11954518 | Caupolicán | Caupolican,Caupolicán | CL | Biobío | -37.55097 | -73.3792 | 0 | America/Santiago | populated place | ||
| 12524920 | San Rafael | San Rafael | CL | Los Lagos Region | -41.72424 | -73.17899 | 0 | America/Santiago | populated place | ||
| 11945822 | Colonia Loncollamo | Colonia Loncollamo | CL | Araucanía | -38.58114 | -73.45954 | 0 | America/Santiago | populated place | ||
| 12004395 | El Llano | El Llano | CL | Maule Region | -35.80847 | -72.30302 | 0 | America/Santiago | populated place | ||
| 11965991 | Villa Alegre | Villa Alegre | CL | Biobío | -36.53886 | -72.74491 | 0 | America/Santiago | populated place | ||
| 11945781 | Calatayu | Calatayu | CL | Araucanía | -38.45477 | -72.34919 | 0 | America/Santiago | populated place | ||
| 3888622 | Guadalao | Guadalao | CL | O’Higgins Region | -34.26548 | -71.54887 | 0 | America/Santiago | populated place | ||
| 12004402 | El Durazno | El Durazno | CL | Maule Region | -35.76459 | -72.09778 | 0 | America/Santiago | populated place | ||
| 11954734 | Cuyinco Bajo | Cuyinco Bajo | CL | Biobío | -37.65835 | -73.42504 | 0 | America/Santiago | populated place | ||
| 11964705 | Tres Esquinas | Tres Esquinas | CL | Maule Region | -36.14817 | -72.29581 | 0 | America/Santiago | populated place | ||
| 11945675 | Santa Silvia | Santa Silvia | CL | Araucanía | -38.23634 | -72.26999 | 0 | America/Santiago | populated place | ||
| 11966912 | Santa Ester | Santa Ester | CL | Biobío | -36.72453 | -72.82695 | 0 | America/Santiago | populated place | ||
| 11915524 | Santa Marta | Santa Marta | CL | Araucanía | -38.23974 | -72.04965 | 0 | America/Santiago | populated place | ||
| 11896919 | Rucadehue | Rucadehue | CL | Araucanía | -39.02578 | -72.32573 | 0 | America/Santiago | populated place | ||
| 12468979 | Ossandón | Ossandon,Ossandón | CL | Valparaíso | -32.23249 | -71.22616 | 0 | America/Santiago | populated place | ||
| 11956206 | Valle Hermoso | Valle Hermoso | CL | Maule Region | -36.02381 | -71.87526 | 0 | America/Santiago | populated place | ||
| 12469508 | Algarrobo Norte | Algarrobo Norte | CL | Valparaíso | -33.32872 | -71.64504 | 0 | America/Santiago | populated place | ||
| 3894526 | Cobquecura | Cobquecura | CL | Ñuble | Provincia de Itata | -36.13251 | -72.79401 | 0 | America/Santiago | populated place | |
| 11956245 | El Llano | El Llano | CL | Maule Region | -36.10969 | -71.65978 | 0 | America/Santiago | populated place | ||
| 12013546 | Falda de la Piedra | Falda de la Piedra | CL | Maule Region | -34.9615 | -72.10921 | 0 | America/Santiago | populated place | ||
| 11965961 | Quirao | Quirao | CL | Biobío | -36.40801 | -72.4853 | 0 | America/Santiago | populated place | ||
| 3885251 | Lanco | Lanco | CL | Los Ríos Region | Provincia de Valdivia | -39.45246 | -72.77117 | 0 | America/Santiago | populated place | |
| 3877146 | Parral | Parral,Parralja,Парраля | CL | Maule Region | Provincia de Linares | -36.14311 | -71.82605 | 26904 | America/Santiago | populated place | |
| 11896918 | Santa Cecilia | Santa Cecilia | CL | Araucanía | -39.01369 | -72.36685 | 0 | America/Santiago | populated place | ||
| 12002453 | Villa Palermo | Villa Palermo | CL | Maule Region | -35.38589 | -72.17645 | 0 | America/Santiago | populated place | ||
| 11949840 | Santa Adriana | Santa Adriana | CL | Biobío | -37.75788 | -72.01671 | 0 | America/Santiago | populated place | ||
| 11954462 | Santa Elena | Santa Elena | CL | Biobío | -37.36636 | -72.52099 | 0 | America/Santiago | populated place | ||
| 11966921 | Las Raíces | Las Raices,Las Raíces | CL | Biobío | -36.70047 | -72.38713 | 0 | America/Santiago | populated place | ||
| 11897457 | Quintrehueque | Quintrehueque | CL | Los Ríos Region | -39.54699 | -73.03665 | 0 | America/Santiago | populated place | ||
| 3882233 | Los Cerrillos | Los Cerrillos | CL | Santiago Metropolitan | Provincia de Santiago | -33.4926 | -70.71185 | 0 | America/Santiago | populated place | |
| 11967003 | El Macal | El Macal | CL | Biobío | -36.90497 | -72.46261 | 0 | America/Santiago | populated place | ||
| 12100381 | El Salto | El Salto | CL | Aysén | -45.42131 | -72.75125 | 0 | America/Santiago | populated place | ||
| 3870294 | Talca | TLX,Tal’ka,Talca,Talka,Talkao,ta er ka,talka,taruka,Τάλκα,Талка,Талька,تالكا,تالکا,ტალკა,タルカ,塔爾卡,탈카 | CL | Maule Region | Provincia de Talca | -35.4264 | -71.65542 | 197479 | America/Santiago | seat of a first-order administrative division | |
| 11966905 | Los Coihues | Los Coihues | CL | Biobío | -36.72636 | -72.90705 | 0 | America/Santiago | populated place | ||
| 11900798 | Momolluco | Momolluco | CL | Araucanía | -39.58534 | -71.56892 | 0 | America/Santiago | populated place | ||
| 11956282 | El Olivo | El Olivo | CL | Maule Region | -36.15343 | -71.76812 | 0 | America/Santiago | populated place | ||
| 12086704 | San Manuel | San Manuel | CL | Aysén | -44.63112 | -72.94093 | 0 | America/Santiago | populated place | ||
| 12004423 | Cajones | Cajones | CL | Maule Region | -35.66839 | -71.83154 | 0 | America/Santiago | populated place | ||
| 11965977 | El Descanso | El Descanso | CL | Biobío | -36.42681 | -72.06422 | 0 | America/Santiago | populated place | ||
| 12440871 | Elisa de Bordos | Elisa de Bordos | CL | Atacama | -27.71888 | -70.18801 | 0 | America/Santiago | populated place | ||
| 3892878 | Curepto | Curepto,Kurepto,ku lei pu tuo,kulebto,kywrptw shyly,kywrybtw,Курепто,كيوريبتو,کیورپتو، شیلی,庫雷普托,쿠렙토 | CL | Maule Region | Provincia de Talca | -35.09166 | -72.01958 | 0 | America/Santiago | populated place | |
| 11917566 | La Palma | La Palma | CL | Araucanía | -38.56009 | -71.71667 | 0 | America/Santiago | populated place |
Chile: A Vertical Geography Demanding Horizontal Data
A Nation Defined by Latitude, Mapped by Precision
From the Atacama Desert in the north to the ice fields of Patagonia in the south, Chile stretches across an extraordinary range of latitudes, climates, and terrains. As a geographer, Chile feels like an open book with a thousand chapters—each city, commune, and province a story waiting to be mapped. But to read this book effectively, we need clean, structured, and accessible data. And that’s where the foundation of geographic analysis begins: with comprehensive, city-level information, now easier to work with than ever—especially thanks to the newly added Excel (xlsx) format.
Understanding Chile’s Urban Mosaic
Chile’s administrative structure is complex yet coherent. It’s composed of 16 regions, subdivided into provinces and further into communes. Urban development clusters along the country’s central spine, but each city—from Arica to Punta Arenas—plays a vital role in the national ecosystem. Understanding these cities in terms of their administrative placement is more than academic—it’s essential for planning, governance, and investment.
That’s why our dataset does more than just list cities—it links each one to its respective region and department (provincia). This structured relationship is crucial to forming a complete spatial understanding of Chile.
The Geographic Coordinates Behind Every Name
Behind every dot on the map lies a precise set of coordinates. In a country as geographically elongated and tectonically dynamic as Chile, latitude and longitude are not just numbers; they’re lifelines. Whether tracking seismic activity, planning renewable energy infrastructure, or responding to natural disasters, location-specific data is indispensable.
Our dataset includes the exact geographic coordinates for each city and commune, giving you the precision to overlay this information with satellite imagery, population heatmaps, or logistics simulations. And while we won’t publish these coordinates in this article, they are readily available in our structured database.
Excel as a Gateway to Geographic Clarity
What sets our offering apart is the emphasis on usability—particularly through Excel (xlsx). While GIS specialists may appreciate SQL and JSON, the majority of users—planners, researchers, government analysts, and even students—work in Excel. It’s the format of clarity, the spreadsheet language that turns complexity into insight.
Now that our Chile city data is available in Excel, anyone can instantly sort by region, filter by department, and visualize relationships without needing advanced tools. Excel empowers users to explore geographic data without friction, and in a country as layered as Chile, that accessibility is game-changing.
Multi-Format Availability for a Multidisciplinary Landscape
In addition to Excel, our database is accessible in several key formats to accommodate a wide range of technical needs:
* CSV for rapid integration into dashboards or lightweight applications
* SQL for scalable data modeling and enterprise-level systems
* JSON for developers building mapping or web-based tools
* XML for legacy platforms and structured parsing tasks
But Excel remains the flagship—a universal key to unlocking Chile’s urban and administrative geography.
Why Chile’s Cities Matter Now
Chile is not static; it is urbanizing, digitizing, and adapting. Cities like Santiago, Valparaíso, and Concepción are not only hubs of commerce—they are testing grounds for smart infrastructure and green urban planning. Meanwhile, smaller cities along the Andes or the southern fjords are increasingly relevant to biodiversity research, indigenous affairs, and tourism strategy.
With our database, you can move from macro observations to micro decisions—planning a renewable energy project in Coquimbo or analyzing education access in Biobío. This is data not for decoration, but for action.
Conclusion
Chile’s geography demands both admiration and rigor. It’s not enough to marvel at its mountains, deserts, and coastlines; we must understand how its cities are embedded within this natural frame. Our comprehensive, city-level dataset—now enriched by an easy-to-use Excel format—gives researchers, developers, and decision-makers the tools to engage with Chile on a deeper level. It’s more than a database; it’s an invitation to see the country not just as a vertical strip on the globe, but as a living, organized, mappable system of human activity and natural context.
