Lot 52881736 · MN - MINNEAPOLIS NORTH

2016 MERCEDES-BENZ E E350-4M

VIN WDDHF8JB7GB191307

Current bid
$300
≈ €278

The vehicle

  • Year 2016
  • Make / model MERCEDES-BENZ E
  • Trim level E350-4M
  • Body type Sedan/Saloon
  • Condition CERT OF TITLE-SALVAGE
  • VIN WDDHF8JB7GB191307
  • Drive type AWD/All-Wheel Drive
  • Exterior color white
  • Odometer 52,115 mi (83,871 km)
  • Listing valid until 2026-09-15 20:00
Notes
Този Mercedes-Benz E-Class от 2016 г. е стилен и надежден седан с 4x4 задвижване. Умерени щети по дясната задна част на автомобила. 🚗 2016 Mercedes-Benz E-Class седан 📋 Основни характеристики: пробег в км: 83871 задвижване: 4x4 ℹ️ Допълнителна информация: каросерия: седан цвят: бял
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Damage assessment

Body zones

AI-detected zones are pre-marked below — click a zone to adjust its severity.

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Underbody
Condition assessment 1 AI-written variant

gpt-5.6-luna

The auction record lists the vehicle as having a salvage title (“CERT OF TITLE-SALVAGE”) with “SIDE” as the primary damage classification. Stage 1 reports that the visible scraped and deformed lower right side supports the auction’s unverified SIDE damage claim; however, the salvage-title status cannot be confirmed from exterior photographs alone. The main visible damage is concentrated on the lower right side. The lower right rear door and adjacent rocker panel have a broad scrape with white paint loss, dark exposed material, and localized surface deformation. The right rear bumper corner has a split with a jagged opening, scraped paint, and an irregular damaged edge. A long dark surface scuff is also visible along the lower left rear bumper. According to the VIN decode, this is a 2016 Mercedes-Benz E-Class sedan, specifically an E350-4M, manufactured in Germany. It is equipped with all-wheel drive, a 3.5-liter gasoline V6 engine, and four doors. A physical inspection is recommended to assess any underlying structural, suspension, wheel-alignment, bumper-support, sensor, or mechanical damage not established by the available findings, as well as the quality and extent of any previous repairs.

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