TT719 M10 x 1.25 Bolt Black Swing Arm Spool Sliders for CFMOTO Ibex 450/675 – CNC-Machined

Overview

TT719 introduces a purpose-built swing arm spool slider set crafted for CFMOTO Ibex riders who value maintenance ease and a clean, integrated look. The design emphasizes a direct, tool-free fit that requires no modifications, helping you keep your bike ready for the next ride.

Key benefits

• Custom design: Precision engineered for direct-fit installation with no modification needed, so you can mount and go.
• Easy chain maintenance: Lift the rear wheel safely to create clear space for cleaning, lubrication, and adjustment without fuss.
• Premium materials: Built from lightweight yet durable 6061-T6 aluminum, offering solid support during maintenance, storage, and transport while resisting heavy wear.
• Precision CNC machined: Tight tolerances deliver accurate threading, stable mounting, and consistent alignment, helping the bike sit level during service.
• Durable anodized finish: Scratches, corrosion, and fading are kept at bay, maintaining a clean, premium look even with frequent use.

Performance and use cases

During routine upkeep, the spool sliders provide a dedicated mounting point to lift the rear wheel safely. This creates practical working clearance for chain cleaning, lubrication, and adjustment, reducing strain on supports and helping you work more confidently.

The black anodized surface combines durability with a sleek appearance, making the setup both functional and visually cohesive with the bike environment.

Compatibility and fit

The TT719 kit is designed for CFMOTO Ibex 450 variants—including 450, 450SS, 450NK—and the 675-series (675SS, 675NK), covering model years from 2023 through 2026. This broad compatibility supports riders across different trim levels seeking a secure maintenance solution.

Why choose TT719

With a focus on precise fit, durable materials, and simple maintenance integration, this kit aims to support your workflow without altering your bike’s setup. The benefits described reflect feature strengths from the data and illustrate possibilities rather than guarantees.