Lot 54395676 · TX - FT. WORTH
2014 MERCEDES-BENZ GLK GLK350
VIN WDCGG5HB2EG190812
Current bid
$250
≈ €231
Archive
The vehicle
- Year 2014
- Make / model MERCEDES-BENZ GLK
- Trim level GLK350
- Body type Sport Utility Vehicle [SUV]/Multipurpose Vehicle [MPV]
- Condition SALVAGE VEHICLE TITLE
- VIN WDCGG5HB2EG190812
- Engine GLK350 2wd ['13-'15] (3.5-liter M276 60° GDI V6)
- Exterior color white
- Odometer 215,207 mi (346,341 km)
- Listing valid until 2026-07-21 20:00
Notes
Този Mercedes-Benz GLK от 2014 г. е истински джип, готов за нови приключения.
Минорно повърхностно увреждане по бронята и фаровете.
🚗 2014 MERCEDES-BENZ GLK джип
📋 Основни характеристики:
пробег: 346 341 км
двигател: 2.1 L, 4 цилиндъра, 170 к.с.
задвижване: 4x4
ℹ️ Допълнителна информация:
автоматична скоростна кутия, 7-степенна
каросерия: джип
цвят: бял
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Damage assessment
Body zones
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Underbody
Condition assessment
The vehicle is a 2014 Mercedes-Benz GLK being offered with a salvage vehicle title. The auction lists hail as the primary damage. However, Stage 1 reports that the visible hood and rear hatch surfaces are largely smooth and do not show the dense pattern of small shallow dents typically expected from hail. The roof was not shown clearly enough for a complete assessment, so its condition remains unconfirmed. Based on the provided photos, the visible evidence does not support the hail primary-damage claim.
Observed cosmetic findings include several dark scuff marks and linear scratches on the lower left corner of the rear bumper, along with shorter dark scratches on the lower right portion. Light gray scuffing is also visible along the lower side trim beneath the doors. Both front headlamp lenses appear cloudy and discolored.
The driver’s seat shows moderate upholstery wear. The light-colored leather or leather-like material on the outer bolster is cracked, abraded, and peeling, with a longitudinal tear or split in the lower cushion area. No additional damage or mechanical findings were provided.
Generated from auction photos by AI vision, then written up by an AI model. Findings are qualitative, not a certified inspection.