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Cost of living index > Property price index > Most expensive cities in Asia by property price index

2025 - Most Expensive Cities In Asia By Property Price Index

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Top Cities with the most expensive property prices in Asia 2025

Descending rankings:

Cities with the most expensive property prices in Asia

Rankings

Cities with the most expensive property prices in Asia Cities with the most expensive utilities in Asia Cities with the most expensive mobile services in Asia Cities with the most expensive internet service in Asia Cities with the most expensive apartment prices in Asia Cities with the most expensive rent prices in Asia Cities with the highest mortgage rates in Asia

Ascending rankings:

Cities with the cheapest property prices in Asia

Rankings

Cities with the cheapest property prices in Asia Cities with the cheapest utilities in Asia Cities with the cheapest mobile service in Asia Cities with the cheapest internet service in Asia Cities with the cheapest apartment prices in Asia Cities with the cheapest rent in Asia Cities with the lowest mortgage rates in Asia

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Ranking

Indicators

#

Place

Cities

Asian ranking

Property price index

Most expensive first

Cost of living index

The more, the higher prices

Rent to salary ratio

Rent/Salary
🏅 1
🇭🇰   Hong Kong, Hong Kong
85.87
73.47
0.47
🥈 2
🇸🇬   Singapore, Singapore
85.03
82.53
0.53
🥉 3
🇰🇷   Seoul, South Korea
63.41
32.92
0.25
4
🇷🇺   Moscow, Russia
59.03
27.78
0.49
5
🇰🇷   Daegu, South Korea
54.10
28.99
0.22
6
🇨🇳   Shanghai, China
40.36
27.28
0.30
7
🇲🇴   Mação, Macao
36.89
33.11
0.51
8
🇹🇲   Ashgabat, Turkmenistan
36.57
63.11
1.84
9
🇰🇷   Busan, South Korea
36.49
27.58
0.21
10
🇰🇷   Suwon-si, South Korea
35.93
24.83
0.17
11
🇰🇷   Incheon, South Korea
35.39
28.58
0.21
12
🇨🇳   Beijing, China
34.22
26.25
0.28
13
🇨🇳   Shenzhen, China
32.29
25.40
0.26
14
🇹🇱   Dili, Timor-Leste
31.97
41.98
0.32
15
31.37
20.35
0.52
16
🇲🇻   Malé, Maldives
30.49
38.56
0.77
17
🇺🇿   Fergana, Uzbekistan
29.33
17.71
0.23
18
🇮🇳   Mumbai, India
27.54
22.58
0.46
19
🇰🇷   Gwangju, South Korea
26.81
27.37
0.23
20
🇹🇼   Taipei, Taiwan
26.70
26.35
0.29
21
🇵🇰   Quetta, Pakistan
26.62
12.70
2.10
22
🇷🇺   Vladivostok, Russia
23.63
19.18
0.72
23
🇺🇿   Tashkent, Uzbekistan
23.49
21.60
0.94
24
🇯🇵   Tokyo, Japan
23.28
34.80
0.30
25
🇯🇵   Kawasaki, Japan
22.56
32.38
0.22
26
🇷🇺   Kazan, Russia
22.38
16.30
0.62
27
🇰🇷   Daejeon, South Korea
21.88
26.03
0.22
28
🇯🇵   Kyoto, Japan
21.67
27.00
0.25
29
🇱🇰   Colombo, Sri Lanka
21.63
18.86
0.97
30
🇹🇭   Phuket, Thailand
21.09
29.47
0.77
31
🇨🇳   Guangzhou, China
20.61
21.46
0.29
32
🇰🇿   Almaty, Kazakhstan
20.57
21.15
0.76
33
🇵🇭   Manila, Philippines
19.83
21.62
0.73
34
🇹🇼   Taoyuan, Taiwan
19.63
23.00
0.38
35
18.78
18.25
0.74
36
🇷🇺   Barnaul, Russia
18.28
15.69
0.80
37
🇰🇬   Bishkek, Kyrgyzstan
18.07
18.94
1.06
38
🇹🇭   Bangkok, Thailand
17.94
23.82
0.54
39
🇹🇭   Kalasin, Thailand
17.67
15.54
0.60
40
17.55
16.19
0.56
41
🇨🇳   Suzhou, China
17.25
21.48
0.30
42
🇻🇳   Hanoi, Vietnam
17.10
17.68
0.69
43
🇷🇺   Rostov-on-Don, Russia
16.83
20.80
0.87
44
🇨🇳   Tianjin, China
16.38
19.24
0.31
45
🇷🇺   Yekaterinburg, Russia
16.30
17.02
0.63
46
🇹🇼   Taichung, Taiwan
16.30
21.52
0.25
47
🇷🇺   Ufa, Russia
16.14
14.53
0.53
48
🇷🇺   Irkutsk, Russia
16.11
17.68
0.71
49
15.98
18.16
0.62
50
🇰🇭   Phnom Penh, Cambodia
15.89
22.01
1.11
51
🇵🇭   Taguig, Philippines
15.80
23.58
0.83
52
🇰🇿   Shymkent, Kazakhstan
15.70
15.35
0.89
53
🇹🇭   Nonthaburi, Thailand
15.62
19.56
0.29
54
🇰🇷   Ulsan, South Korea
15.49
24.01
0.15
55
🇯🇵   Yokohama, Japan
15.40
29.80
0.24
56
🇯🇵   Saitama, Japan
15.23
23.64
0.21
57
🇷🇺   Novosibirsk, Russia
15.03
16.42
0.60
58
🇷🇺   Khabarovsk, Russia
14.83
18.79
0.62
59
🇯🇵   Kobe, Japan
14.48
25.69
0.27
60
🇯🇵   Osaka, Japan
14.43
28.33
0.27
61
🇷🇺   Omsk, Russia
14.21
14.76
0.53
62
🇹🇭   Samut Prakan, Thailand
14.17
17.17
0.37
63
🇵🇰   Faisalabad, Pakistan
14.00
10.53
0.60
64
🇹🇼   Kaohsiung, Taiwan
13.90
22.70
0.33
65
🇹🇭   Yala, Thailand
13.70
16.54
0.32
66
🇹🇭   Samut Sakhon, Thailand
13.46
24.08
0.72
67
🇵🇭   Batangas, Philippines
13.45
16.09
1.46
68
🇳🇵   Kathmandu, Nepal
13.41
13.70
0.62
69
🇨🇳   Wuhan, China
13.33
20.13
0.36
70
13.01
48.19
1.01
71
13.00
20.36
0.61
72
🇷🇺   Krasnodar, Russia
12.96
15.44
0.51
73
🇯🇵   Sapporo, Japan
12.19
30.22
0.45
74
🇱🇦   Vientiane, Laos
12.06
34.70
3.74
75
🇷🇺   Volgograd, Russia
11.88
14.30
0.67
76
🇷🇺   Tolyatti, Russia
11.69
14.55
0.73
77
🇮🇳   Surat, India
11.66
24.38
1.35
78
🇵🇰   Lahore, Pakistan
11.57
13.61
1.02
79
🇨🇳   Chengdu, China
11.44
16.43
0.25
80
🇵🇭   Cebu City, Philippines
11.40
19.98
0.75
81
🇮🇳   Delhi, India
11.39
16.24
0.28
82
🇲🇳   Ulaanbaatar, Mongolia
11.33
24.24
1.17
83
🇻🇳   Can Tho, Vietnam
11.33
12.41
1.05
84
🇺🇿   Samarkand, Uzbekistan
11.32
14.32
0.70
85
🇮🇩   Surabaya, Indonesia
11.23
15.79
0.73
86
🇻🇳   Hải Dương, Vietnam
11.22
15.76
0.52
87
🇻🇳   Da Nang, Vietnam
11.19
16.05
0.67
88
🇮🇳   Bengaluru, India
11.11
16.33
0.17
89
🇦🇿   Baku, Azerbaijan
10.99
19.24
0.66
90
🇮🇩   Jakarta, Indonesia
10.87
19.33
0.62
91
🇹🇯   Dushanbe, Tajikistan
10.81
17.00
1.75
92
🇷🇺   Saratov, Russia
10.64
14.02
0.56
93
🇵🇭   Bulakan, Philippines
10.57
15.15
0.66
94
🇲🇾   Kuala Lumpur, Malaysia
10.54
20.43
0.26
95
🇨🇳   Xi'An, China
10.46
17.49
0.30
96
🇯🇵   Nagoya, Japan
10.30
28.31
0.22
97
🇺🇿   Nukus, Uzbekistan
10.17
18.76
1.36
98
🇵🇭   Caloocan, Philippines
9.95
19.83
1.44
99
🇹🇼   Tainan, Taiwan
9.91
19.31
0.20
100
9.85
47.37
0.63
101
🇵🇰   Rawalpindi, Pakistan
9.84
11.89
0.86
102
🇷🇺   Chelyabinsk, Russia
9.74
14.48
0.64
103
🇮🇩   Bekasi, Indonesia
9.46
14.98
0.49
104
🇹🇭   Chiang Mai, Thailand
9.19
19.25
0.43
105
9.05
10.93
0.22
106
🇵🇰   Gujranwala, Pakistan
9.05
9.64
0.49
107
🇷🇺   Makhachkala, Russia
8.91
15.82
0.91
108
🇲🇾   Johor Bahru, Malaysia
8.79
19.18
0.41
109
🇮🇳   Hyderabad, India
8.54
15.21
0.18
110
🇨🇳   Chongqing, China
8.42
16.26
0.25
111
🇮🇳   Chennai, India
7.65
14.40
0.19
112
🇵🇰   Karachi, Pakistan
7.43
13.42
1.21
113
🇮🇳   Ahmedabad, India
7.31
15.09
0.36
114
🇮🇩   Sidoarjo, Indonesia
7.00
11.38
0.64
115
🇰🇿   Karaganda, Kazakhstan
6.91
15.38
0.51
116
🇺🇿   Namangan, Uzbekistan
6.88
11.92
0.51
117
🇮🇩   Tangerang, Indonesia
6.83
15.68
0.85
118
🇦🇿   Sumqayit, Azerbaijan
6.79
15.67
0.56
119
🇮🇩   Medan, Indonesia
6.58
14.45
0.67
120
🇰🇿   Aktobe, Kazakhstan
6.55
14.14
1.02
121
🇮🇳   Lucknow, India
6.54
13.48
0.33
122
6.48
16.46
0.53
123
🇧🇩   Gazipur, Bangladesh
6.45
10.39
0.40
124
🇻🇳   Haiphong, Vietnam
6.41
16.10
0.54
125
🇦🇫   Herat, Afghanistan
6.28
16.57
1.29
126
🇮🇩   Depok, Indonesia
6.03
11.21
0.20
127
🇻🇳   Bien Hoa, Vietnam
5.93
12.24
0.51
128
🇲🇾   Klang, Malaysia
5.71
17.48
0.40
129
🇧🇩   Dhaka, Bangladesh
5.70
12.69
0.36
130
🇺🇿   Bukhara, Uzbekistan
5.56
13.31
0.36
131
🇮🇳   Kolkata, India
5.22
12.66
0.25
132
🇦🇫   Kabul, Afghanistan
5.04
14.61
0.54
133
🇮🇳   Jaipur, India
4.84
13.28
0.23
134
🇮🇩   Bandung, Indonesia
4.77
13.65
0.69
135
🇧🇩   Chattogram, Bangladesh
4.66
11.36
0.30
136
🇵🇰   Peshawar, Pakistan
4.01
11.20
0.69
137
3.27
15.64
0.70
138
🇵🇰   Multan, Pakistan
2.88
11.72
0.61

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