Kandersteg

City in Bern, Switzerland

Overview

Kandersteg is a picturesque alpine village set in the Bernese Oberland, known for pristine lakes, mountain scenery, and world-class hiking. With a small, welcoming community, it is a tranquil escape for nature enthusiasts and families.

Geographic Context

Jurisdiction
Switzerland
Canton
Bern
Population
1,298
Time Zone
Europe/Zurich
Coordinates
46.49°, 7.67°

Key Metrics

Safety Score · estimate
93
Female Safety
90
LGBTQ+ Safety
80
Traffic Safety
93
Food Safety
99
Monthly Cost · estimate
$2,465
Local Cost
$1,830
Local Income
$4,200
Cashless
85
English
75
Temperature
4.0°C
Summer Avg
12.9°C
Winter Avg
-5.0°C
Record High
27.6°C
Record Low
-26.5°C
Humidity
81%
Precipitation
1176 mm
Internet Speed
86 Mbps
Upload
26 Mbps
Latency
12 ms
City Vibrancy
—
Coworking
0
Cafes
0
Nightlife
0
Parks
0
Transport
18
Walk Score
18
Footways
35.0
Airport
SIR
Distance
40 km

Data sources

Source-backed data

Ookla Open Data - Internet speed aggregates for 2024Q3 from 10 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 2026-03-22.
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: 80/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.