Lot 45666728 · Los Angeles South

2025 MERCEDES-BENZ MAYBACH EQS 680 SUV 4MATIC

VIN 4JGDX5FB5SA039436

IAAI Listing ended Salvage Large Electric Rear Run & Drive
Price
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The vehicle

  • Year 2025
  • Make / model MERCEDES-BENZ MAYBACH EQS 680 SUV
  • Trim level 4MATIC
  • Series / platform code 4MATIC
  • Body type Sport Utility Vehicle [SUV]/Multipurpose Vehicle [MPV]
  • Condition Salvage
  • VIN 4JGDX5FB5SA039436
  • Drive type All-Wheel Drive
  • Transmission Automatic
  • Horsepower 649 к.с.
  • Powertrain Battery electric
  • Exterior color Black
  • Odometer 4,253 mi (6,845 km)
  • Listing valid until 2026-09-16
Notes
Луксозният Mercedes-Maybach EQS 680 SUV от 2025 година е тук, за да ви впечатли с мощност и комфорт. Има леки повреди по задната броня. Автомобилът стартира и се движи. 🚗 2025 Mercedes-Maybach EQS 680 SUV 4MATIC 📋 Основни характеристики: пробег: 6 845 км двигател: 649 к.с. задвижване: 4x4 ℹ️ Спецификация: скоростна кутия: автоматична каросерия: джип цвят: черен ключове: налични
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Damage assessment

Body zones

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Underbody
Condition assessment 1 AI-written variant

gpt-5.6-luna

The auction lists the primary damage as rear. Stage 1’s assessment is that this claim is partially supported by visible minor surface scuffing on the lower rear bumper; no substantial rear deformation or broken rear components were visible. The recorded damage is limited to minor cosmetic abrasion. Light-colored scuff marks are present on the lower right section of the rear bumper near and below the reflector and lower trim, including the lower rear bumper corner. No other damage findings were provided. VIN decoding identifies the vehicle as a 2025 Mercedes-Benz EQS-Class SUV, Maybach EQS 680 4MATIC trim, with all-wheel drive and a battery-electric powertrain using an electric motor. The decoded engine output is 649 hp. The vehicle is classified as a multipurpose passenger vehicle/SUV and was manufactured by Mercedes-Benz of North America in Vance, Alabama, USA.

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