
EuroBillTracker (EBT) is a website designed for tracking euro banknotes. It was inspired by the US currency bill tracking website Where's George? The aim is to record as many notes as possible to know details about their distribution and movements, follow it up, like where a note has been seen in particular, and generate statistics and rankings, for example, in which countries there are more tickets. EuroBillTracker has registered over 243 million notes with a combined total value of more than €4.4 billion as of February 2026.
via Wikipedia infobox
EuroBillTracker (EBT) is a website designed for tracking euro banknotes. It was inspired by the US currency bill tracking website Where's George? The aim is to record as many notes as possible to know details about their distribution and movements, follow it up, like where a note has been seen in particular, and generate statistics and rankings, for example, in which countries there are more tickets. EuroBillTracker has registered over 243 million notes with a combined total value of more than €4.4 billion as of February 2026.
== Characteristics == EuroBillTracker is an international non-profit volunteer team dedicated to tracking euro notes around the world. The site is made up of people who simply enter the information from the notes in their possession. Each user enters the serial numbers and location information for each note they obtain into EuroBillTracker. A user can then see any comments from other people who have had that note. From this information, the site extracts: Diffusion information: Each euro country has its own range of note serial numbers and from this information EBT can generate diffusion graphs that tell us how the notes travel to other countries. See the Diffusion section for more information. Tracking information: When a note is re-entered, the users who previously entered it are notified via email. These hits can be seen in the statistics section. Statistics and rankings: Who enters the most notes, which are the top countries? Where are the notes currently situated?
Discovered by embedding cosine similarity (sentence-transformers MiniLM, 384-dim).