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Montenegro
City in Rio Grande do Sul, Brazil
Overview
Montenegro is a charming city in Rio Grande do Sul, Brazil, known for its strong German heritage, tree-lined avenues, and dynamic local culture. While relatively compact, the city offers a thriving food scene, preserved historic structures, and a welcoming community.
Geographic Context
Jurisdiction
Brazil
State
Rio Grande do Sul
Population
66,352
Time Zone
America/Sao_Paulo
Coordinates
-29.69°, -51.46°
Key Metrics
Safety Score
55
Female Safety
60
LGBTQ+ Safety
40
Traffic Safety
65
Food Safety
70
Monthly Cost
$633
Local Cost
$378
Local Income
$430
Cashless
45
English
30
Temperature
18.7°C
Summer Avg
23.2°C
Winter Avg
14.0°C
Record High
39.5°C
Record Low
-2.1°C
Humidity
81%
Precipitation
1574 mm
Internet Speed
258 Mbps
Upload
215 Mbps
Latency
5 ms
City Vibrancy
13
Coworking
0
Cafes
1
Nightlife
0
Parks
12
Transport
0
Walk Score
0
Footways
—
Airport
QNS
Distance
42 km
Explore
Neighborhoods
Mapped31 neighborhoods sourced from Overture Maps and OpenStreetMap.
View all 31 neighborhoodsFrequently Asked Questions
Data sources
Source-backed data
NASA POWER - Climate normals and monthly weather measurements rendered as city weather metrics. Updated 2026-03-22.
World Air Quality Index - Latest available city-level air quality station measurement. Updated 2025-12-05.
Ookla Open Data - Internet speed aggregates for 2024Q3 from 28 tests. Updated 2025-12-05.
OpenStreetMap - Nearby amenities counted from OpenStreetMap-derived city extracts. Updated 2025-12-06.
OpenStreetMap transport extract - Walkability, footway density, and airport access metrics derived from mapped transport features. Updated 2025-12-05.
Oyster List city price model - City price estimates calibrated from local price surveys and jurisdiction-level cost signals. Updated 2026-01-14.
Overture Maps and OpenStreetMap - 31 source-backed neighborhood entities are available for this city. Updated 2026-04-04.
Estimated data
Oyster List AI-assisted estimates - Safety, lifestyle, income, and practical scores are model-assisted estimates derived from source-backed country and city signals. Confidence 68/100.
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