#1006 -30 HAYDEN ST N Toronto, ON
$ 2,200
Property Attributes
  • ID#C5153814
  • TypeRentals
  • CityToronto
  • NeighbourhoodChurch-Yonge Corridor
  • Postal CodeM4Y 3B8
  • StyleApartment
  • Price$ 2,200
  • Bedrooms2
  • Full Bathrooms1
  • Half Bathrooms0
Listing Provided Courtesy Of:
Jack Penk with Bridlepath Progressive Real Estate Inc.
Data Source:
Property Description

Welcome To This Beautiful 2 Bedroom Bright And Very Spacious Corner Unit In Shane Baghai's Ultra Luxurious Building At Yonge And Bloor. This Unit Has Very Spacious Bedrooms, Open Concept Floor Plan, Kitchen Overlooking The Living/Dining Room. 2 Walk Out Balconies With A Beautiful View Of The Toronto Skyline. Unit Has Laminate Flooring And Is Excellent Condition. Subway Entrance Is Right Beside The Entrance Of The Building**** EXTRAS **** Fridge, Stove, Washer/Dryer, Microwave, B/I Dishwasher,One Parking Included In The Rent. (id:27)

General Features

Amenities Exercise Centre, Recreation Centre
Beds 2
Building Type Apartment
Features Balcony
Garage no
Listing Type Condo
Neighbourhood Church-Yonge Corridor
Parking no
Property Type Single Family
Wheel Chair Access no

Interior Features

Bedrooms 2
Bedrooms Above 2
Cooling Type Central air conditioning
Fireplace no
Heating Fuel Natural gas
Heating Type Forced air
Total Baths 1

Exterior Features

Exterior Finish Concrete
Parking Type Underground
Pool Y/N no

Room Details

Room Dimensions Level Flooring Details
2nd Bedroom 2.87 m x 2.59 m Flat/Apartment Level
Dining 7.15 m x 3.35 m Flat/Apartment Level
Kitchen 2.44 m x 2.35 m Flat/Apartment Level
Living 7.15 m x 3.35 m Flat/Apartment Level
Master Bedroom 3.66 m x 2.82 m Flat/Apartment Level


  • Views
  • New Construction
  • Adult 55+
  • Lease To Own
  • No Strata Fees
  • Furnished
  • Pets
  • Master On Main
  • Air Conditioning
  • Seller Finance
  • Green
  • Fixer Upper
  • Horse
  • Golf
  • Fireplace
  • Deck
  • Garage
  • Basement
  • Pool

Property vs Postal Code Average in M4Y 3B8

AVG 25
AVG 98
Data Provided by Walkscore ® not using MLS data