# TranslateLocally: Blazing-fast translation running on the local CPU

arXiv: https://arxiv.org/abs/2109.10194 · HTML: https://mlsanity.com/paper/2109.10194/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 15 references that are in the map.
- First posted on arXiv 21 Sep 2021.

## Builds on (most cited first, 4 of 4)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Neural Machine Translation by Jointly Learning to Align and Translate](https://mlsanity.com/paper/1409.0473/) (2014)
- [Sequence-Level Knowledge Distillation](https://mlsanity.com/paper/1606.07947/) (2016)
- [Marian: Fast Neural Machine Translation in C++](https://mlsanity.com/paper/1804.00344/) (2018)

## Built on by (most cited first, 3 of 3)

- [PyMarian: Fast Neural Machine Translation and Evaluation in Python](https://mlsanity.com/paper/2408.11853/) (2024)
- [Defending Against Authorship Identification Attacks](https://mlsanity.com/paper/2310.01568/) (2023)
- [sign.mt: Real-Time Multilingual Sign Language Translation Application](https://mlsanity.com/paper/2310.05064/) (2023)

## Abstract (arXiv)

Every day, millions of people sacrifice their privacy and browsing habits in exchange for online machine translation. Companies and governments with confidentiality requirements often ban online translation or pay a premium to disable logging. To bring control back to the end user and demonstrate speed, we developed translateLocally. Running locally on a desktop or laptop CPU, translateLocally delivers cloud-like translation speed and quality even on 10 year old hardware. The open-source software is based on Marian and runs on Linux, Windows, and macOS.