Lot 61680036 · SC - NORTH CHARLESTON
2016 MERCEDES-BENZ GL GL450-4M
VIN 4JGDF6EE0GA697550
Current bid
$1,750
≈ €1,620
Archive
The vehicle
- Year 2016
- Make / model MERCEDES-BENZ GL
- Trim level GL450-4M
- Body type Sport Utility Vehicle [SUV]/Multipurpose Vehicle [MPV]
- Condition CERTIFICATE OF TITLE
- VIN 4JGDF6EE0GA697550
- Horsepower 362 к.с.
- Exterior color white
- Odometer 145,825 mi (234,682 km)
- Listing valid until 2026-08-31 17:00
Notes
Този Mercedes-Benz GL от 2016 г. е просторен и мощен SUV, готов за нови приключения.
Леки щети по задната част.
🚗 2016 MERCEDES-BENZ GL
📋 Основни характеристики:
пробег: 234 682 км
двигател: 3.0 L, 6 цилиндъра, 362 к.с.
задвижване: 4x4
ℹ️ Допълнителна информация:
каросерия: джип
цвят: бял
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Damage assessment
Body zones
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Underbody
Condition assessment
Auction records list the vehicle’s condition as “Certificate of Title” and the primary damage as “Rear End.” However, the Stage 1 photo review states that the photos do not support a rear-end primary-damage claim: the rear exterior appears intact apart from a minor cosmetic scuff on the left rear bumper. Certificate-of-title status cannot be verified from the photos.
The visible damage is limited to a short, horizontal dark abrasion on the white left rear bumper cover below the left tail lamp. This is classified as minor cosmetic damage. The steering-wheel rim also shows visible smoothing and wear to the leather surface in several areas, likewise classified as minor cosmetic wear.
The VIN decodes to a 2016 Mercedes-Benz GL-Class SUV, trim designation GL450-4M, equipped with a turbocharged 3.0-liter M276 gasoline V6 producing 362 horsepower. The vehicle was manufactured by Mercedes-Benz of North America in the United States. The drivetrain and transmission details were not provided by the VIN decoding data.
No mechanical or structural condition can be established from these findings. A physical inspection should confirm the bumper condition, title status, and overall vehicle condition before purchase.
Generated from auction photos by AI vision, then written up by an AI model. Findings are qualitative, not a certified inspection.