Lot 49286926 · TX - CORPUS CHRISTI

2017 MERCEDES-BENZ GLS GLS450-4M

VIN 4JGDF6EE3HA789320

Price
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The vehicle

  • Year 2017
  • Make / model MERCEDES-BENZ GLS
  • Trim level GLS450-4M
  • Body type Sport Utility Vehicle [SUV]/Multipurpose Vehicle [MPV]
  • Condition CERTIFICATE OF TITLE
  • VIN 4JGDF6EE3HA789320
  • Horsepower 362 к.с.
  • Exterior color dark gray
  • Odometer 128,856 mi (207,373 km)
  • Listing valid until 2026-09-22 20:00
Engine sound

Engine start-up clip from the auction listing -- not an independent inspection.

Notes
Мерцедес GLS от 2017 година – стил и комфорт в един SUV. Двигателят стартира и работи сравнително гладко, като се долавя леко почукване, което може да изисква допълнителна проверка. 🚗 2017 MERCEDES-BENZ GLS 📋 Основни характеристики: пробег: 207 373 км двигател: 3.0 L, 6 цилиндъра, 362 к.с. задвижване: 4x4 ℹ️ Допълнителна информация: каросерия: джип цвят: тъмносив
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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 2017 Mercedes-Benz GLS-Class SUV, identified by VIN 4JGDF6EE3HA789320. The provided VIN decode identifies the GLS450-4M trim with a turbocharged 3.0-liter M276 gasoline V6 engine rated at 362 horsepower. The vehicle was manufactured by Mercedes-Benz of North America in Vance, Alabama, USA. No specific damage findings were provided. The auction record lists the vehicle’s condition as “Certificate of Title” and its primary damage as “Hail.” These are unverified auction classifications. Stage 1’s photo review found that the visible evidence does not support the hail claim: the hood and rear hatch appeared largely smooth, with no dense pattern of small shallow dents, and no apparent hail-dent pattern was visible on the partially visible roof. No visible hail damage was identified in the provided photos. A physical inspection is recommended to check areas not visible in the photos and to verify the vehicle’s overall mechanical and structural condition.

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