Tamiya XF80 Royal Light Gray (81780) Acrylic paint 10ml – model acrylic paint

Tamiya XF80 Royal Light Gray (81780) is a high-quality acrylic paint, created especially for demanding modelers who value precision and excellent reproduction of historical and modern vehicle colors. This product is widely used in the modeling field, especially for painting plastic model kits, resin models, and elements made using 3D printing. The 10 ml capacity makes it an ideal amount for both large modeling projects and small details.

The Royal Light Gray color is often used in military, aviation, and naval modeling – from tanks and military aircraft to World War II ships and Cold War era aircraft models. It perfectly reflects historical colors used by the United Kingdom, such as the Royal Navy or Royal Air Force, especially for painting aircraft carrier decks or fuselages of planes like the Supermarine Spitfire and Hawker Hurricane.

• Capacity: 10 ml
• Type: Water-based acrylic paint
• Manufacturer: Tamiya
• Color: Royal Light Gray (XF80)
• Category: Model acrylic paints
• Product material: High-quality mixture of acrylic pigments and dispersive resins
• Application: Painting plastic models, resin models, miniatures/figures (scales 1/35, 1/48, 1/72 and others)
• Recommended thinner: Tamiya X-20A and Tamiya Retarder
• Ease of use: 1/5 (very easy to apply, ideal for beginners and advanced modelers)

The formula of this paint makes it extremely efficient and chip-resistant. It is especially recommended for application with a brush or airbrush. Thanks to its appropriate consistency, it provides even coverage and is easy to level. Tamiya XF80 paint dries quickly and allows for a matte, authentic finish. As a result, modelers achieve an effect true to the original, which translates into the realism of the finished project.

We recommend it to modelers of all skill levels. Excellent for dioramas, military vehicles, aircraft, and warships. Tamiya XF80 Royal Light Gray is an essential element of every modeler's workshop who values top quality, durable results, and historical accuracy in models.