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Oulad Tayeb
City in Fès-Meknès, Morocco
Overview
Oulad Tayeb is a peaceful suburb just outside the city of Fès in Fès-Meknès, Morocco, known for its relaxed pace and authentic Moroccan charm. The town offers a local experience with traditional markets and easy access to the cultural sights of the region. It's a perfect base for travelers seeking tranquility while remaining close to Fès.
Geographic Context
Jurisdiction
Morocco
Region
Fès-Meknès
Population
—
Time Zone
Africa/Casablanca
Coordinates
33.95°, -5.00°
Key Metrics
Safety Score · estimate
60
Female Safety
50
LGBTQ+ Safety
30
Traffic Safety
55
Food Safety
70
Monthly Cost · estimate
$565
Local Cost
$310
Local Income
$275
Cashless
20
English
20
Temperature
18.6°C
Summer Avg
27.5°C
Winter Avg
10.7°C
Record High
46.0°C
Record Low
-3.9°C
Humidity
58%
Precipitation
715 mm
Internet Speed
46 Mbps
Upload
35 Mbps
Latency
22 ms
City Vibrancy
—
Coworking
0
Cafes
0
Nightlife
0
Parks
0
Transport
2
Walk Score
2
Footways
4.0
Airport
FEZ
Distance
2 km
Explore
Data sources
Source-backed data
OpenStreetMap - Nearby amenities counted from OpenStreetMap-derived city extracts. Record updated 2025-12-09.
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: 38/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.
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