Lot 61067096 · ON - TORONTO
2016 PORSCHE MACAN
VIN WP1AB2A57GLB44771
Current bid
C$925
≈ €625
Archive
The vehicle
- Year 2016
- Make / model PORSCHE MACAN
- Series / platform code S
- Body type Sport Utility Vehicle [SUV]/Multipurpose Vehicle [MPV]
- Condition PERMIT NO BRAND - FIT (P)
- VIN WP1AB2A57GLB44771
- Horsepower 340 к.с.
- Engine 3.0L twin-turbo Porsche M46.30 90 degree V6, 340 hp (Macan S)
- Exterior color blue
- Odometer 0 mi (0 km)
- Listing valid until 2026-07-21 17:00
Notes
Този Porsche Macan от 2016 г. е чудесен избор за всеки, който търси стил и динамика.
Леки козметични забележки по предната лява врата.
🚗 2016 Porsche Macan, SUV
📋 Основни характеристики:
година на производство: 2016
марка: Porsche
модел: Macan
каросерия: джип
цвят: син
ℹ️ Допълнителна информация:
състояние: PERMIT NO BRAND - FIT (P)
основна щета: VANDALISM
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Damage assessment
Body zones
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Underbody
Condition assessment
The auction records list the vehicle as having a “PERMIT NO BRAND - FIT (P)” condition and classify the primary damage as vandalism. However, the available photo review found that the visible photos do not support the unverified vandalism claim; no clear vandalism damage is visible. The permit/no-brand/fit status also cannot be confirmed from the photos.
The only visible damage is a minor paint chip or scuff on the exterior of the left front door. It appears as a small, light-colored mark on the blue paint near the middle-lower area of the door.
An official NHTSA recall applies to 2015–2018 Porsche Macan vehicles, including this 2016 model, under campaign 20V077000. The recall concerns possible cracking of the fuel pump flange, which may cause a fuel leak and increase the risk of fire if an ignition source is present. The remedy involves inspection and, where necessary, replacement or rework of the fuel pump flange, along with protective film installation. Recall completion should be verified with Porsche or through the vehicle’s service records before purchase.
Generated from auction photos by AI vision, then written up by an AI model. Findings are qualitative, not a certified inspection.