Lot 54858886 · NC - RALEIGH
2016 MERCEDES-BENZ S S550-4M
VIN WDDUG8FB3GA210929
Price
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The vehicle
- Year 2016
- Make / model MERCEDES-BENZ S
- Trim level S550-4M
- Body type Sedan/Saloon
- Condition SALVAGE CERTIFICATE OF TITLE
- VIN WDDUG8FB3GA210929
- Engine S550 4Matic sedan ['14-'17] (4.7-liter twin turbo M278 GDI V8)
- Exterior color white
- Odometer 115,927 mi (186,566 km)
- Listing valid until още не е насрочена
Notes
Този Mercedes-Benz S-Class от 2016 г. е истинска класика в луксозния сегмент, предлагаща комфорт и стил.
Тежък удар в предната част на автомобила.
🚗 2016 Mercedes-Benz S седан
📋 Основни характеристики:
пробег в км: 186566
каросерия: седан
цвят: бял
ℹ️ Допълнителна информация:
Няма налична информация за допълнителни характеристики.
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Damage assessment
Body zones
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Underbody
Condition assessment
The vehicle is a 2016 Mercedes-Benz S-Class sedan with a salvage certificate of title. The auction lists the primary damage as FRONT END. Stage 1 reports that the visible evidence supports this claim: the front bumper, grille, lower fascia, and both front fenders are missing, leaving front-end components exposed.
The front bumper cover, front grille, and lower front fascia are absent. Both the left and right front fenders are missing, exposing the front wheels, inner fender areas, mounting components, and other front-end structures. Wiring and connectors are visibly exposed and hanging in the open front-end area. The left rocker molding is displaced and separated from the body along the forward portion of the lower side.
The VIN decode identifies the vehicle as a gasoline-powered 4.7-liter V8 Mercedes-Benz S-Class, trim S550-4M, manufactured in Sindelfingen, Germany. The decoded safety equipment includes front, side, and curtain airbags, as well as seat-belt pretensioners and load limiters. The extent of the visible front-end damage means that additional inspection is required to assess hidden structural, cooling, electrical, suspension, and safety-system damage before repair or road use.
Generated from auction photos by AI vision, then written up by an AI model. Findings are qualitative, not a certified inspection.