Lot 59828906 · GA - SAVANNAH
2016 MERCEDES-BENZ S S550-4M
VIN WDDUG8FB4GA236309
Current bid
$2,000
≈ €1,852
Archive
The vehicle
- Year 2016
- Make / model MERCEDES-BENZ S
- Trim level S550-4M
- Body type Sedan/Saloon
- Condition CERT OF TITLE-SALVAGE
- VIN WDDUG8FB4GA236309
- Engine S550 4Matic sedan ['14-'17] (4.7-liter twin turbo M278 GDI V8)
- Exterior color dark blue
- Odometer 51,212 mi (82,418 km)
- Listing valid until 2026-07-27 17:00
Notes
Този Mercedes-Benz S-Class от 2016 г. е истинска находка за ценителите на лукса.
Леки щети по задната броня.
🚗 2016 Mercedes-Benz S-Class седан
📋 Основни характеристики:
пробег: 82 418 км
двигател: 3.0 L, 6 цилиндъра, 362 к.с.
задвижване: задно
ℹ️ Допълнителна информация:
каросерия: седан
цвят: тъмносин
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Damage assessment
Body zones
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Underbody
Condition assessment
The auction record lists the vehicle as having a salvage title and identifies the primary damage as “REAR END.” Stage 1 reports that the visible evidence supports this claim only to the extent of localized rear-bumper scuffing and scratches; no clear major rear-end deformation was visible in the provided photos. Stage 1 also notes that the salvage-title status cannot be confirmed from the photos.
The documented exterior damage consists of several light-colored abrasion marks and minor scuffing on the lower left rear bumper corner. On the right side, multiple horizontal white abrasion marks, scratches, and areas of surface scuffing extend across the rear bumper corner and into the adjacent rear quarter-panel area. This right-side damage is assessed as moderate.
VIN decoding identifies the vehicle as a 2016 Mercedes-Benz S-Class sedan, S550-4M trim, equipped with a gasoline 4.7-liter V8 engine. The vehicle was manufactured by Mercedes-Benz Cars in Sindelfingen, Germany. The available data does not specify the transmission or drivetrain. Further inspection is recommended to assess the bumper structure, quarter-panel, mounting points, sensors, and any damage not visible in the provided images.
Generated from auction photos by AI vision, then written up by an AI model. Findings are qualitative, not a certified inspection.