Coxim
City in Mato Grosso do Sul, Brazil
Overview
Coxim is a riverside town in Mato Grosso do Sul, acting as a gateway to the northern Pantanal wetlands. It boasts a laid-back pace, lively local culture, and easy access to outdoor adventures along the scenic Coxim and Taquari rivers.
Geographic Context
Jurisdiction
Brazil
State
Mato Grosso do Sul
Population
33,440
Time Zone
America/Sao_Paulo
Coordinates
-18.51°, -54.76°
Key Metrics
Safety Score · estimate
55
Female Safety
50
LGBTQ+ Safety
35
Traffic Safety
50
Food Safety
60
Monthly Cost · estimate
$810
Local Cost
$480
Local Income
$370
Cashless
40
English
20
Temperature
26.7°C
Summer Avg
27.4°C
Winter Avg
24.5°C
Record High
45.3°C
Record Low
5.0°C
Humidity
63%
Precipitation
1076 mm
Internet Speed
173 Mbps
Upload
205 Mbps
Latency
4 ms
City Vibrancy
6
Coworking
0
Cafes
1
Nightlife
0
Parks
5
Transport
1
Walk Score
1
Footways
1.0
Airport
—
Distance
—
Explore
Data sources
Source-backed data
World Air Quality Index - Latest available city-level air quality station measurement. Record updated 2025-12-05.
OpenStreetMap - Nearby amenities counted from OpenStreetMap-derived city extracts. Record updated 2025-12-06.
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 2026-03-22.
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: 60/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.