Slab Contrasted Urly 8 is a bold, wide, medium contrast, upright, normal x-height font visually similar to 'FF More' by FontFont, 'Mundo Serif' by Monotype, 'Leida' by The Northern Block, and 'Portada' by TypeTogether (names referenced only for comparison).
Keywords: headlines, posters, editorial, packaging, branding, sturdy, industrial, classic, authoritative, impact, readability, heritage, solidity, authority, slabbed, bracketed, meaty, ink-trap free, high-contrast serifs.
A robust slab-serif with pronounced, blocky serifs and gently bracketed joins that soften the otherwise muscular construction. Strokes are thick and confident with noticeable—but not extreme—contrast, giving rounds and verticals a slightly sculpted feel. Counters are compact and the overall color is dark and even, helped by strong horizontals and squared terminals. Letterforms lean traditional and proportional, with clear serifs on capitals and a solid, workmanlike lowercase that holds together well in dense text.
Best suited to headlines, deck type, and short blocks of copy where strong serif structure and dark typographic color are assets. It also fits editorial layouts, packaging, and branding systems that want a traditional slab-serif tone with high impact and clear structure.
The tone is steady and authoritative, combining a traditional bookish sensibility with an industrial, hard-working presence. It reads as confident and dependable rather than delicate, lending a serious, editorial voice with a hint of vintage heft.
Likely designed to deliver a bold, legible slab-serif voice that feels classic yet forceful, emphasizing strong silhouettes and dependable readability. The combination of bracketed slabs and controlled contrast suggests an aim for editorial versatility with assertive presence.
The heavy slabs and compact internal spaces create strong texture on the page, especially in all-caps and bold settings. Numerals appear sturdy and straightforward, matching the weight and presence of the letters for consistent emphasis in headings and data-like contexts.