TT Norms Std Condensed Thin
Similar fonts
- 888 Semi Condensed Thin
- Aktiv Grotesk Cd Deva Hair Italic
- Aktiv Grotesk Cd Trial Hair Italic
- AlergiaCondensed-Hairline
- Amsi Pro Narrow Thin
- Ashemore Cond Thin Italic
- Blackbird Test Narrow Thin
- CoreSansR-15Thin
- Corporative Sans Alt Cnd Hair
- CorporativeSansCnd-Hair
- CorpSansRdAlt-HairCnd
- Elza-NarrowThinOblique
- FSP DEMO - Peridot LT Narw Thin Regular
- FSP DEMO - TT Nrms Pr Cnd Thn Italic
- GrotaSansRounded-Regular11
- Iosevka NF Thin
- Iosevka Term Slab Thin
- IosevkaTerm NFP Thin
- Komplekt 050 Thin Italic
- Neusa Next Pro Condensed Thin Italic
- Onsite Condensed_STJ3 Thin Italic
- OT Neue Montreal Thin Italic Semi Squeezed
- PP Pangram Sans Rounded Condensed Thin
- SanukOT-Hairline
- Spezia Narrow Light Italic
- Spezia Narrow TEST FONT Thin Italic
- Squick-Thin
- St Transmission 200 Thin
- StratumNo1-Thin
- Super Sans Condensed Hairline
- TT Norms Std Trl Cnd Thin Italic
- VinylOT-Outline
- VLDekarLight
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.