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Sibul

City in Central Luzon, Philippines

Overview

Sibul is a tranquil town in Central Luzon best known for its refreshing hot springs and welcoming local atmosphere. With its small population and peaceful vibe, it offers travelers a genuine escape from urban hustle and a window into rural Filipino life.

Geographic Context

Jurisdiction
Philippines
Region
Central Luzon
Population
8,225
Time Zone
Asia/Manila
Coordinates
15.17°, 121.06°

Key Metrics

Safety Score · estimate
60
Female Safety
50
LGBTQ+ Safety
25
Traffic Safety
45
Food Safety
60
Monthly Cost · estimate
$487
Local Cost
$267
Local Income
$220
Cashless
20
English
65
Temperature
25.3°C
Summer Avg
26.1°C
Winter Avg
23.5°C
Record High
38.4°C
Record Low
16.0°C
Humidity
86%
Precipitation
2832 mm
Internet Speed
140 Mbps
Upload
88 Mbps
Latency
22 ms
City Vibrancy
—
Coworking
0
Cafes
0
Nightlife
0
Parks
0
Transport
1
Walk Score
1
Footways
1.0
Airport
—
Distance
—

Data sources

Source-backed data

Ookla Open Data - Internet speed aggregates for 2024Q3 from 41 tests. Record updated 2025-12-05.
OpenStreetMap - Nearby amenities counted from OpenStreetMap-derived city extracts. Record updated 2025-12-07.
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: 65/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.

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