Lot 56796346 · NV - LAS VEGAS WEST

2016 MERCEDES-BENZ C C300

VIN 55SWF4JB6GU128947

Price
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The vehicle

  • Year 2016
  • Make / model MERCEDES-BENZ C
  • Trim level C300
  • Body type Sedan/Saloon
  • Condition SALVAGE TITLE
  • VIN 55SWF4JB6GU128947
  • Engine C300 sedan (2.0-liter turbocharged GDI M274 I4)
  • Exterior color white
  • Odometer 79,605 mi (128,112 km)
  • Listing valid until 2026-07-27 22:00
Notes
Този Mercedes-Benz C-Class от 2016 г. е стилен седан в бял цвят, готов за нов собственик. Умерени щети по дясната страна на автомобила. 🚗 2016 MERCEDES-BENZ C-Class седан 📋 Основни характеристики: пробег 128 112 км каросерия седан цвят бял ℹ️ Допълнителна информация: няма данни
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Damage assessment

Body zones

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Underbody
Condition assessment 1 AI-written variant

gpt-5.6-luna

The vehicle is a 2016 Mercedes-Benz C-Class C300 sedan. Auction records list it as having a salvage title with “SIDE” recorded as the primary damage. Stage 1 reports that the visible right-side door and rocker-panel damage supports the “SIDE” classification; the salvage-title status cannot be confirmed or contradicted from exterior photographs alone. The lower sections of the right-side front and rear doors have broad dark scuffing, scraped paint, and localized deformation. The right-side rocker panel below the doors shows extensive scraping and paint loss, together with irregular deformation. These areas represent moderate collision damage and will require repair assessment, including inspection for possible damage behind the exterior panels and to the rocker structure. According to the VIN decode, this is a U.S.-built 2016 Mercedes-Benz C300 with a 2.0-liter, four-cylinder gasoline engine. The decoded safety equipment includes front airbags, side airbags for the first and second rows, curtain airbags, pretensioners, load limiters, and direct tire-pressure monitoring. Further physical inspection is recommended before purchase to assess structural condition, door operation, and the full scope of repairs.

Generated from auction photos by AI vision, then written up by an AI model. Findings are qualitative, not a certified inspection.