In 2025, 88.8% of Volkswagen Taigo MOT tests were passed first time, about the same as the 88.7% for cars of the same age. 4.4% had at least one dangerous defect (3.6% for cars the same age). The typical Volkswagen Taigo tested was 3 years old with 22,400 miles. Based on 5,672 initial MOT tests in Great Britain.
Volkswagen TaigoAll cars first registered that year
Year first registered
Tests
First-time pass
All cars
2023
408
90.4%
91.7%
2022
5,257
88.7%
88.5%
Years with fewer than 30 tests are left out.
Great Britain · DVSA MOT tests · 2025
By age at the test
Volkswagen TaigoAll cars that age
Age
Tests
First-time pass
All cars
Typical miles
3-4 years
3,694
88.5%
87.4%
22,800
Great Britain · DVSA MOT tests · 2025
Where they’re tested
Colour shows how common the Volkswagen Taigo is among cars tested in each area, against its share across Great Britain: 2× means twice as common as usual.
under 0.5×
0.5×–0.8×
0.8×–1.25×
1.25×–2×
2× or more
Fewer than 5 tests
None tested
Postcode area of the garage that did the test, not where the owner lives. Hover over or tap an area for its figures.
Postcode area
Region
Tests
Share
vs all cars
First-time pass
G Glasgow
Scotland
171
3.0%
1.9×
87.1%
B Birmingham
West Midlands
160
2.8%
0.9×
86.9%
LE Leicester
East Midlands
153
2.7%
1.5×
76.5%
EH Edinburgh
Scotland
122
2.2%
1.7×
86.1%
AB Aberdeen
Scotland
115
2.0%
2.7×
85.2%
S Sheffield
Yorkshire and the Humber
113
2.0%
0.9×
92.9%
M Manchester
North West
112
2.0%
1.3×
88.4%
PE Peterborough
East of England
111
2.0%
1.1×
91.0%
L Liverpool
North West
108
1.9%
1.7×
83.3%
CV Coventry
West Midlands
107
1.9%
1.3×
95.3%
CH Chester
North West
105
1.9%
1.7×
91.4%
WA Warrington
North West
104
1.8%
1.8×
88.5%
SK Stockport
North West
103
1.8%
1.8×
88.3%
NE Newcastle upon Tyne
North East
97
1.7%
1.0×
90.7%
CF Cardiff
Wales
86
1.5%
0.9×
83.7%
BL Bolton
North West
85
1.5%
2.0×
94.1%
CM Chelmsford
East of England
83
1.5%
1.2×
86.7%
DD Dundee
Scotland
82
1.4%
3.5×
81.7%
DE Derby
East Midlands
78
1.4%
1.0×
92.3%
NG Nottingham
East Midlands
78
1.4%
0.7×
91.0%
SA Swansea
Wales
78
1.4%
1.1×
93.6%
LS Leeds
Yorkshire and the Humber
72
1.3%
1.1×
79.2%
KY Kirkcaldy
Scotland
66
1.2%
2.1×
97.0%
RH Redhill
South East
66
1.2%
1.1×
90.9%
BB Blackburn
North West
64
1.1%
1.3×
93.8%
PO Portsmouth
South East
63
1.1%
0.8×
82.5%
ME Rochester
South East
61
1.1%
1.0×
91.8%
MK Milton Keynes
South East
61
1.1%
1.0×
90.2%
NN Northampton
East Midlands
61
1.1%
0.8×
93.4%
BD Bradford
Yorkshire and the Humber
58
1.0%
1.1×
87.9%
LL Llandudno
Wales
58
1.0%
1.1×
93.1%
OX Oxford
South East
56
1.0%
0.9×
94.6%
WF Wakefield
Yorkshire and the Humber
55
1.0%
1.1×
90.9%
PA Paisley
Scotland
54
1.0%
2.1×
85.2%
PR Preston
North West
54
1.0%
1.0×
94.4%
BS Bristol
South West
53
0.9%
0.5×
75.5%
HU Hull
Yorkshire and the Humber
52
0.9%
1.3×
86.5%
SO Southampton
South East
51
0.9%
0.7×
86.3%
DN Doncaster
Yorkshire and the Humber
50
0.9%
0.7×
86.0%
OL Oldham
North West
50
0.9%
1.3×
96.0%
ST Stoke-on-Trent
West Midlands
50
0.9%
0.8×
82.0%
TN Tonbridge
South East
50
0.9%
0.7×
88.0%
DL Darlington
North East
49
0.9%
1.5×
89.8%
YO York
Yorkshire and the Humber
49
0.9%
0.9×
95.9%
ML Motherwell
Scotland
48
0.8%
1.7×
85.4%
NP Newport
Wales
48
0.8%
1.0×
87.5%
NR Norwich
East of England
48
0.8%
0.6×
91.7%
RG Reading
South East
48
0.8%
0.6×
81.2%
GU Guildford
South East
47
0.8%
0.6×
91.5%
IP Ipswich
East of England
47
0.8%
0.7×
89.4%
EX Exeter
South West
46
0.8%
0.7×
89.1%
GL Gloucester
South West
46
0.8%
0.7×
89.1%
BN Brighton
South East
45
0.8%
0.7×
95.6%
CO Colchester
East of England
45
0.8%
1.0×
86.7%
DA Dartford
South East
44
0.8%
1.1×
86.4%
DH Durham
North East
44
0.8%
1.6×
90.9%
CW Crewe
North West
42
0.7%
1.2×
90.5%
HP Hemel Hempstead
South East
42
0.7%
0.8×
95.2%
KT Kingston upon Thames
London
42
0.7%
0.9×
97.6%
AL St Albans
East of England
41
0.7%
1.6×
97.6%
RM Romford
London
41
0.7%
0.9×
97.6%
SP Salisbury
South West
41
0.7%
1.5×
85.4%
WR Worcester
West Midlands
41
0.7%
1.2×
82.9%
BA Bath
South West
40
0.7%
0.8×
80.0%
CA Carlisle
North West
40
0.7%
1.2×
97.5%
HR Hereford
West Midlands
40
0.7%
1.9×
100.0%
KA Kilmarnock
Scotland
40
0.7%
1.3×
77.5%
CR Croydon
London
39
0.7%
1.0×
94.9%
SY Shrewsbury
West Midlands
39
0.7%
1.0×
97.4%
BH Bournemouth
South West
38
0.7%
0.6×
84.2%
SG Stevenage
East of England
37
0.7%
0.9×
89.2%
TS Teesside
North East
37
0.7%
0.7×
86.5%
IV Inverness
Scotland
36
0.6%
1.5×
91.7%
NW London NW
London
35
0.6%
0.9×
88.6%
WV Wolverhampton
West Midlands
35
0.6%
0.9×
85.7%
BR Bromley
London
33
0.6%
1.6×
78.8%
SL Slough
South East
33
0.6%
0.8×
93.9%
PL Plymouth
South West
32
0.6%
0.6×
90.6%
TW Twickenham
London
31
0.5%
0.8×
77.4%
FY Blackpool
North West
30
0.5%
1.3×
100.0%
SS Southend-on-Sea
East of England
30
0.5%
0.6×
90.0%
CT Canterbury
South East
29
0.5%
0.7×
–
FK Falkirk
Scotland
29
0.5%
1.2×
–
TR Truro
South West
29
0.5%
0.8×
–
HD Huddersfield
Yorkshire and the Humber
28
0.5%
1.2×
–
LA Lancaster
North West
27
0.5%
0.9×
–
HA Harrow
London
26
0.5%
0.8×
–
LN Lincoln
East Midlands
26
0.5%
0.8×
–
WN Wigan
North West
26
0.5%
1.0×
–
SE London SE
London
25
0.4%
0.6×
–
N London N
London
24
0.4%
0.6×
–
TF Telford
West Midlands
24
0.4%
1.1×
–
WD Watford
East of England
24
0.4%
1.1×
–
PH Perth
Scotland
23
0.4%
1.4×
–
SN Swindon
South West
23
0.4%
0.5×
–
IG Ilford
London
21
0.4%
0.8×
–
TQ Torquay
South West
20
0.4%
0.7×
–
HG Harrogate
Yorkshire and the Humber
19
0.3%
1.2×
–
WS Walsall
West Midlands
19
0.3%
0.5×
–
DY Dudley
West Midlands
18
0.3%
0.5×
–
EN Enfield
London
17
0.3%
0.5×
–
HX Halifax
Yorkshire and the Humber
16
0.3%
1.1×
–
SR Sunderland
North East
16
0.3%
0.8×
–
CB Cambridge
East of England
14
0.2%
0.4×
–
DT Dorchester
South West
14
0.2%
0.6×
–
SW London SW
London
14
0.2%
0.6×
–
UB Southall
London
14
0.2%
0.4×
–
E London E
London
11
0.2%
0.2×
–
LU Luton
East of England
11
0.2%
0.3×
–
DG Dumfries
Scotland
10
0.2%
0.8×
–
TD Galashiels
Scotland
9
0.2%
0.8×
–
TA Taunton
South West
8
0.1%
0.2×
–
HS Outer Hebrides
Scotland
fewer than 5
–
–
–
KW Kirkwall
Scotland
fewer than 5
–
–
–
LD Llandrindod Wells
Wales
fewer than 5
–
–
–
SM Sutton
London
fewer than 5
–
–
–
W London W
London
fewer than 5
–
–
–
ZE Shetland
Scotland
fewer than 5
–
–
–
Region
Tests
Share
vs all cars
First-time pass
Scotland
810
14.3%
1.8×
86.8%
North East
243
4.3%
1.1×
89.7%
North West
950
16.7%
1.4×
90.5%
Yorkshire and the Humber
512
9.0%
1.0×
88.7%
Wales
273
4.8%
1.0×
89.4%
West Midlands
533
9.4%
1.0×
89.5%
East Midlands
396
7.0%
1.0×
85.6%
East of England
491
8.7%
0.9×
90.2%
London
378
6.7%
0.7×
90.5%
South East
696
12.3%
0.8×
89.7%
South West
390
6.9%
0.7×
85.9%
Great Britain · DVSA MOT tests · 2025
Where they fail
Share of tests with at least one failure in each area, against cars of the same age.
Volkswagen TaigoCars the same age
Tyres4.3%4.8%
Brakes3.0%1.4%
Visibility (wipers, glass, mirrors)2.2%2.6%
Seat belts and airbags1.5%0.3%
Lights and electrics1.2%2.5%
Suspension0.7%0.7%
Emissions and leaks0.3%0.4%
Body and structure0.1%0.2%
Steering0.1%0.1%
A test can fail in more than one area. Failures fixed during the test are included.
Great Britain · DVSA MOT tests · 2025
Most common failures
The 10 defects that failed Volkswagen Taigo tests most often, as a share of all tests.
Failure
Tests
Cars the same age
vs same age
Marked dangerous
Brake pads: less than 1.5 mm thick Brakes Dangerous
2.3%
0.8%
2.9×
100.0%
Condition: has a cut in excess of the requirements deep enough to reach the ply or cords Tyres
2.0%
2.0%
1.0×
0.0%
Wipers: does not clear the windscreen effectively Visibility (wipers, glass, mirrors)
1.3%
1.7%
0.8×
0.0%
Tread depth: tread depth below requirements of 1.6mm Tyres Dangerous
1.0%
1.1%
0.9×
100.0%
Condition: not functioning as intended Seat belts and airbags
0.8%
0.1%
8.0×
0.0%
Condition: has ply or cords exposed Tyres Dangerous
0.7%
1.0%
0.7×
100.0%
Headlamp aim: too high Lights and electrics
0.5%
0.8%
0.6×
0.0%
Condition: buckle not functioning as intended Seat belts and airbags
0.4%
0.1%
4.0×
0.0%
Washers: not working Visibility (wipers, glass, mirrors)
“vs same age” compares this model with cars of the same age: 2.0× means twice as often. “Marked dangerous” is how often the tester recorded that failure as dangerous.
Great Britain · DVSA MOT tests · 2025
Most common advisories
Things the tester noted to watch, which don’t fail the test.
Advisory
Tests
Tread depth: worn close to legal limit/worn on edge
11.8%
Brake pads: wearing thin
10.5%
Brake discs: worn, pitted or scored, but not seriously weakened
5.8%
Condition: slightly damaged/cracking or perishing
5.3%
Non-component advisories: Child Seat fitted not allowing full inspection of adult belt
3.4%
Non-component advisories: Nail in tyre
2.3%
Condition: has a cut but not deep enough to reach the ply or cords
1.8%
Brake discs: worn, but not excessively
1.6%
Non-component advisories: Items removed from driver's view prior to test
0.8%
Registration plates: deteriorated but not likely to be misread
To provide the best experiences, we use technologies like cookies to store and/or access device information. Consenting to these technologies will allow us to process data such as browsing behaviour or unique IDs on this site. Not consenting or withdrawing consent, may adversely affect certain features and functions.
Functional
Always active
The technical storage or access is strictly necessary for the legitimate purpose of enabling the use of a specific service explicitly requested by the subscriber or user, or for the sole purpose of carrying out the transmission of a communication over an electronic communications network.
Preferences
The technical storage or access is necessary for the legitimate purpose of storing preferences that are not requested by the subscriber or user.
Statistics
The technical storage or access that is used exclusively for statistical purposes.The technical storage or access that is used exclusively for anonymous statistical purposes. Without a subpoena, voluntary compliance on the part of your Internet Service Provider, or additional records from a third party, information stored or retrieved for this purpose alone cannot usually be used to identify you.
Marketing
The technical storage or access is required to create user profiles to send advertising, or to track the user on a website or across several websites for similar marketing purposes.