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Limbang
City in Sarawak, Malaysia
Overview
Limbang is a charming riverside town in northern Sarawak, Malaysia, set between Brunei's two exclaves. It is known for its relaxed atmosphere, lively markets, and cultural diversity influenced by Malay, Chinese, and indigenous communities.
Geographic Context
Jurisdiction
Malaysia
State
Sarawak
Population
38,093
Time Zone
Asia/Kuala_Lumpur
Coordinates
4.75°, 115.00°
Key Metrics
Safety Score · estimate
65
Female Safety
60
LGBTQ+ Safety
35
Traffic Safety
60
Food Safety
75
Monthly Cost · estimate
$480
Local Cost
$217
Local Income
$350
Cashless
40
English
35
Temperature
27.3°C
Summer Avg
27.7°C
Winter Avg
26.8°C
Record High
32.1°C
Record Low
23.0°C
Humidity
83%
Precipitation
2988 mm
Internet Speed
125 Mbps
Upload
35 Mbps
Latency
21 ms
City Vibrancy
21
Coworking
0
Cafes
18
Nightlife
0
Parks
3
Transport
0
Walk Score
0
Footways
—
Airport
LMN
Distance
6 km
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 2025-12-05.
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: 70/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.
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