Lot 54818986 · IN - FORT WAYNE
2013 MERCEDES-BENZ GLK GLK350 4-MATIC
VIN WDCGG8JB2DG071636
Current bid
$250
≈ €231
Archive
The vehicle
- Year 2013
- Make / model MERCEDES-BENZ GLK
- Trim level GLK350 4-MATIC
- Body type Sport Utility Vehicle [SUV]/Multipurpose Vehicle [MPV]
- Condition CERTIFICATE OF TITLE
- VIN WDCGG8JB2DG071636
- Drive type AWD/All-Wheel Drive
- Engine GLK350 4Matic ['13-'15] (3.5-liter M276 60° GDI V6)
- Exterior color white
- Odometer 143,307 mi (230,630 km)
- Listing valid until 2026-07-20 17:00
Notes
Този Mercedes-Benz GLK от 2013 г. е готов за нов собственик.
Има тежки щети по предната част.
🚗 2013 MERCEDES-BENZ GLK
📋 Основни характеристики:
пробег в км: 230630
ℹ️ Допълнителна информация:
каросерия: джип
цвят: бял
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Damage assessment
Body zones
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Underbody
Condition assessment
The vehicle is a 2013 Mercedes-Benz GLK. The auction record lists the primary damage as “FRONT END,” and the visible evidence supports this classification. The front-left headlamp assembly is severely broken, with the outer lens and surrounding sections missing or damaged and internal components exposed. The front-left bumper corner is also severely cracked and displaced, with a detached section and components visible behind it.
Additional front-end damage includes a moderately deformed front-left hood corner, an irregular gap above the headlamp area, and creasing and deformation of the front-left fender around the headlamp opening and upper wheel arch. Multiple dark scuff marks are present on the damaged bumper corner.
Inside the vehicle, the driver’s seat leather upholstery has moderate wear damage, including extensive cracking, peeling, and an open tear along the outer bolster and adjacent lower cushion.
The auction condition is listed as “CERTIFICATE OF TITLE.” This status cannot be verified from the available photos. A physical inspection is recommended to assess any concealed damage, the condition of components behind the damaged front end, and the extent of required repairs.
Generated from auction photos by AI vision, then written up by an AI model. Findings are qualitative, not a certified inspection.