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

2025 - Cheapest Cities In Asia By Property Price Index

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Top Cities with the cheapest 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 cheapest first

Cost of living index

The more, the higher prices

Rent to salary ratio

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

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