Gargantilla

City in Caceres, Spain

Overview

Gargantilla is a charming, tranquil village set in the province of Cáceres, Spain. Known for its scenic landscapes, friendly locals, and traditional stone architecture, it's perfect for visitors seeking authentic rural experiences in Extremadura.

Geographic Context

Jurisdiction
Spain
Province
Caceres
Population
364
Time Zone
Europe/Madrid
Coordinates
40.25°, -5.92°

Key Metrics

Safety Score · estimate
88
Female Safety
82
LGBTQ+ Safety
65
Traffic Safety
86
Food Safety
97
Monthly Cost · estimate
$1,190
Local Cost
$716
Local Income
$1,150
Cashless
28
English
28
Temperature
15.7°C
Summer Avg
26.3°C
Winter Avg
6.5°C
Record High
44.7°C
Record Low
-5.3°C
Humidity
60%
Precipitation
435 mm
Internet Speed
307 Mbps
Upload
134 Mbps
Latency
10 ms
City Vibrancy
5
Coworking
0
Cafes
1
Nightlife
1
Parks
3
Transport
3
Walk Score
3
Footways
5.0
Airport
—
Distance
—

Data sources

Source-backed data

Ookla Open Data - Internet speed aggregates for 2024Q3 from 8 tests. Record updated 2025-12-05.
OpenStreetMap - Nearby amenities counted from OpenStreetMap-derived city extracts. Record updated 2025-12-08.
OpenStreetMap transport extract - Walkability, footway density, and airport access metrics derived from mapped transport features. Record updated 2025-12-06.

Estimates and unverified origins

Oyster List climate data - Climate origins are unverified. Available methods include historical APIs and AI estimates; stored rows do not identify the original dataset, reference period, or model for each value. Treat these summaries as estimates until independently verified. Record updated 2026-03-23.
Oyster List city price estimates - Price origins are unverified. Available generation methods include AI estimates; stored records do not identify a survey, observation period, or model for each price. Record updated 2026-01-14.
Oyster List AI-assisted estimates - Safety, lifestyle, income, and practical scores include model-assisted estimates. Stored records do not identify supporting observations for each score. Model-reported confidence: 63/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.