








Nilight Side Shooter LED Light Bar 2PCS 4.3 Inch Triple Row Spot Flood Combo Lights Led Work Light with Wiring Harness Kit for Off Road Fog Light Driving Light on Truck SUV ATV UTV
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Product Details
【Upgrade Side Shooter Design】Designed with side lights at two ends, triple rows of dual sided lights and nested reflector cup design combined beam, 170° flood beam and 30° spot beam, shoots out a 200° wider and further light coverage to clear darkness and potential hazard, increasing your driving safety. Works great as fog lights, side lights, driving lights, etc
【Super Bright】 60W led pod lights, combination of 30 pcs superior-quality chips emit 5800-6000k bright white light, higher light transmission rate polycarbonate lenses - reduce optical loss, delivering 5500 lumens and ensuring that objects far clearly visible to prevent potential threats, offering you an unparalleled driving experience
【Upgrade waterproof structure】 IP67 Waterproof rating, die-cast aluminum alloy shell, waterproof, dustproof, rustproof and shockproof perfect performance. Exclusively designed waterproof grooves and waterproof rubber strips, perfectly die-casting the rubber strips and the shell together, the sealing performance is upgraded, and the waterproof performance is better than ordinary structure lights
【Wide Application】With the working voltage of 9-30V DC, can be widely used on most of vehicles, perfect for different types of Off-road Jeeps, Truck, heavy duty, SUV, ATV, UTV, tractor, boat, etc. Indoor and outdoor uses: Garden Lighting, Backyard Lighting, Back-up Light, Off Road Lighting
【Package Included】: 2 x 4.3 inch side shooter LED light bar, 1x 16 AWG wiring harness kit-2 lead and 1 pack of mounting bracket & hardware
Best Review
Customers find the lights bright and easy to install. They consider them a good value for the price, with simple functionality and no flickering. The rocker switch works great for most customers. While some are satisfied with the look, others have issues with the mount quality and wire length.AI-generated from the text of customer reviews