ASMS
Similar fonts
- AleHouse
- ASMS-Italic
- Avignon Pro Cd
- b52 Nirmaan
- Config Light
- Darwin-ExtraLight
- Datatype Condensed Black
- Datatype Condensed Regular
- Datatype Expanded Bold
- Datatype ExtraCondensed Light
- Datatype ExtraExpanded Bold
- Datatype ExtraExpanded Light
- Datatype SemiExpanded ExtraLight
- Datatype SemiExpanded Regular
- Datatype SemiExpanded Thin
- Fester Regular Italic
- Franie Test Condensed SemiLight Italic
- Google Sans Flex Rounded 9pt UltraCondensed ExtraLight
- GothamXNarrow-BookItalic
- GothamXNarrSSm-BookItalic
- GT Standard Mono Narrow Light Oblique
- Hoxton North Test Light
- InputMonoNarrow LightIta Testing
- Ioskeley Mono NL Light Semi-Condensed
- JetBrainsMonoNL NFP ExtraLight
- Ottessa Regular Italic
- Quan-Book
- Tourney Condensed Regular
- TriplexItalicOT-Light
- TT Interphases Pro Condensed Regular
- TT Polls Light
- UDShinGoCOsezPr6-Reg
- VTF Justina HUM 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.