❄️ Pirelli Scorpion Winter 2 285/40R23 XL 111V Light Truck/SUV Performance Snow Truck Tire
⚡ Price Comparison Summary:
Weekly updated prices from top retailers 2 retailers, the best price for the Pirelli Scorpion Winter 2 285/40R23 XL 111V Light Truck/SUV Performance Snow Truck Tire is $661.45, currently matched by Tire Rack and SimpleTire.$661.45
Unleash formidable winter performance with the Pirelli Scorpion Winter 2, an expertly engineered Light Truck/SUV Performance Snow Truck Tire. This premium tire, specifically in the 285/40R23 XL 111V size, is designed for discerning drivers of high-performance SUVs and light trucks, providing exceptional safety and control when facing the most challenging cold-weather conditions, from heavy snow to icy roads and frigid temperatures.
Experience superior grip and responsive handling thanks to its advanced tread compound and innovative directional pattern, optimized for severe winter environments. The Scorpion Winter 2 ensures precise steering response and outstanding cornering stability, maintaining driver confidence even on slick surfaces, while offering reliable braking performance and robust traction in both wet and dry cold conditions.
Constructed for enduring durability, this tire offers impressive tread life specifically tailored for rigorous winter use and sustained performance. Its robust, XL-rated design withstands harsh elements, providing consistent capability and reliability throughout the entire cold season.
Despite its aggressive winter capabilities, the Pirelli Scorpion Winter 2 delivers a remarkably comfortable and quiet ride, minimizing road noise for a more refined cabin experience on your winter travels.
Key Features & Specifications
- Load Index: 111
- Speed Rating: V
- Season: Winter / Snow
- Tread Pattern: Directional Performance Snow
- Sidewall: XL (Extra Load)
Invest in the Pirelli Scorpion Winter 2 for uncompromising winter performance, superior safety, and unmatched peace of mind on every journey.
Product information is compiled and reviewed by our editorial team using manufacturer specifications and retailer data.

