TFForeverTwoThin-Normal
Similar fonts
- Albura Thin Italic
- Anek Gurmukhi Thin
- ArtifaktElement-Hair
- BebasNeuePro-ExpandedThinItalic
- Branding SF Narrow Thin It
- Cacao Fat Outline PDF
- CANDY CANE DOODLE
- CoreSansD15Thin
- DalleSet-UltraLight
- Drive Mono Hairline Italic
- Drive Prop Hairline Italic
- F37 Mancunio Trial Thin Condensed
- FFMetaPro-HairItalic
- Finador-ThinOblique
- Gardenia-Thin
- GraphikCompactTrial-ThinItalic
- Hype 1300 Thin It
- Iosevka Thin Italic
- Ioskeley Mono NL Thin Semi-Condensed Italic
- Italian Plate No1 Mono Ultralight Italic
- Jiho Thin Italic
- Martian B Thin
- Meta Offc Pro Hairline Italic
- Onsite Standard TRIAL Thin
- Planer-ExtraLight
- PP Pangram Sans Rounded Condensed Thin Italic
- ProfilePro-Thin
- Questline Variable Thin It Ita
- Serca Thin Italic
- Serial_Trial Thin Italic
- TFForever-Thin
- TTHazelnuts-ThinItalic
- Uninsta-Light
Details
How are we calculating this?
We analyze each font added to FontBase locally using the opentype.js library. We render the text off-canvas and measure key characteristics: stroke width; difference between bold and thin strokes; the relation of "x" letter height to capital letters; width of the letters compared to height; "i" size compared to "w" size. From these calculated numbers, we then build weight, proportion, xHeight and contrast. We also analyze the font's naming table to retrieve the basic info like font name, foundry and style names. No fonts are uploaded to our servers in the process.
How do we determine similar fonts?
Based on the characteristics we retrieve, on each font page, we select the fonts that have all the same parameter numbers. For example, if a font has 0.6 weight, we select fonts from our database that are in the range of 0.5-0.7 weight. We do this with all parameters combined, resulting in a similar font selection.