Lot 46178526 · SC - SPARTANBURG
2015 MERCEDES-BENZ GLK GLK350
VIN WDCGG5HB9FG374517
Current bid
$700
≈ €648
Archive
The vehicle
- Year 2015
- Make / model MERCEDES-BENZ GLK
- Trim level GLK350
- Body type Sport Utility Vehicle [SUV]/Multipurpose Vehicle [MPV]
- Condition CERT OF TITLE-SALVAGE
- VIN WDCGG5HB9FG374517
- Exterior color white
- Odometer 142,734 mi (229,708 km)
- Listing valid until 2026-08-10 17:00
Notes
Този Mercedes-Benz GLK от 2015 г. е стилен и надежден джип, готов за нов собственик.
Умерени козметични щети по левите врати и предния капак.
🚗 2015 Mercedes-Benz GLK джип
📋 Основни характеристики:
пробег в км: 229708
каросерия: джип
цвят: бял
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Damage assessment
Body zones
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Underbody
Condition assessment
The auction records list the vehicle as having a salvage title with “FRONT END” as the primary damage classification. Stage 1’s photo-based assessment found limited visible support for this classification: the left front hood edge has an uneven gap, but no substantial front bumper, grille, headlamp, or structural front-end damage was visibly evident. The salvage-title status could not be confirmed from the photos.
The left front door has multiple dark abrasion marks and shallow deformation across its middle and lower sections, including near the rear edge and lower trim. Similar moderate denting and scuffing are present on the left rear door, mainly around the front half and lower section. The left front edge of the hood has a visibly enlarged, uneven gap relative to the left headlamp and front fender, and it is not flush with the adjacent panels.
According to the VIN decode, this is a 2015 Mercedes-Benz GLK-Class GLK350 SUV, built in Germany. It is equipped with a 3.5-liter six-cylinder gasoline engine. The VIN decode identifies front-row driver and passenger airbags, side airbags for the first and second rows, seat-belt pretensioners and load limiters, and direct tire-pressure monitoring. Drive type and transmission details were not provided.
Generated from auction photos by AI vision, then written up by an AI model. Findings are qualitative, not a certified inspection.