Hexting-ExpandedRegular
Similar fonts
- 2BubbleBath-Regular
- ABC Social Greek Extended Unlicensed Trial Hairline Italic
- ABC Social Hairline Italic
- AddressSansPro-ThinIt
- AudibleSans-HrIt
- Bantat W05 SemiCond Thin It
- Bw Modelica SS02 Hairline Expanded Italic
- DSert-ThinItalic
- FSP DEMO - Freigeist Con Thin Italic
- FSP DEMO - RslvSnsltrlghtNrwt Regular
- Gaglio Thin
- GoldenGrotesque-ThinItalic
- Halenoir CompactDispW05UltLtObl
- Harrison Serif Pro Thin Italic
- Ingra Wd Thin
- Janda Sparkle and Shine
- MatahariExt-100ThinObl
- Neue Television S Retro Regular W0 P50
- NeueRemanGt-ExtLtSemCondIta
- NewHildegardPro-Square2
- Normaliq-ThinItalic
- Novel Sans Hair Pro 12
- NoyhSlimHairlineItalic
- Olivetta Thin It
- Omnes Cond Thin
- OmnesCyrillic Cond Thin
- PlanerTrial ExtraLight Italic
- Resolve Sans W05 Ultlight Wide
- Scharf Test Thin
- Scharf-Thin
- Science Gothic MaximumContrast Oblique Expanded Thin
- TheSans Hair H13 Italic
- Typo Grotesk Thin Italic
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.