I find that meta’s translations are very poor compared to others, at least for relatively obscure languages, which I figured was relevant considering the article.
Google Translate is a good default, but LLMs are really good at translations, as they’re better capable at understanding context and providing culturally appropriate translations.
(I live in Cambodia where they speak Khmer)
smallerize•Mar 21, 2026
*they're
(Sorry I had to)
stingraycharles•Mar 21, 2026
I could have sworn I edited it! I did notice myself as well, but thanks for the correction.
tomrod•Mar 21, 2026
*ពួកគេគឺជា
djsamseng•Mar 21, 2026
Hello from Siem Reap, Cambodia! Awesome to see a fellow tech enthusiast from Cambodia.
I actually found Facebook’s translations pretty good (better than Google Translate for things longer than a sentence). From my understanding of Khmer, Khmer is a bit more verbose and context dependent, hence LLMs in Khmer would be a big help understand those nuances.
In the inverse case (LLMs generating khmer from English) I heard from locals that it sounds formal and “robotic” which I found quite interesting.
pseudocomposer•Mar 21, 2026
Kagi Translate is fantastic. Multilingual support is honestly one of the best things about LLMs, imo.
yellow_lead•Mar 21, 2026
It's not even good for Chinese
ks2048•Mar 21, 2026
So, LLMs are noticeably better in Khmer than Google Translate? I wonder why Google Translate doesn't use Gemini under-the-hood. Perhaps it's more prone to hallucinations.
I'm interested in find some thorough testing of translations on different LLMs vs Translation APIs.
pattilupone•Mar 21, 2026
There's a dropdown on Google Translate that lets you choose "Advanced" mode or "Classic" mode. Advanced mode uses Gemini but it's only available for select languages.
psychoslave•Mar 21, 2026
That's a high count, but still a bit away from "Omni". Usual count is between 4k and 8k depending the source. But the first 1k might be the hardest, certainly.
simultsop•Mar 21, 2026
when you market, you use frontier and edge terms, so it sounds pro max
croes•Mar 21, 2026
Off topic, since the AI craze MS‘ documentation translation has ridiculous errors like translating try catch keywords to "versuchen" and "fangen" for German pages
Tarq0n•Mar 21, 2026
Yes their translations offer negative value, which is annoying because at work you can't usually choose your locale settings.
And the errors are really basic, like translating shortly to short, not the same thing at all!
bikeshaving•Mar 21, 2026
I’m very wary of celebrating Meta’s language work when the company was credibly found to have contributed to the genocide against the Rohingya in Myanmar, and separately, to human rights abuses against Tigrayans during the conflict in northern Ethiopia. Be careful whose sins you’re laundering.
They can translate 1600 languages, but they cannot do basic text formatting, where are the paragraphs?
canjobear•Mar 21, 2026
It's an abstract for a paper, so it's officially supposed to be one paragraph.
BalinKing•Mar 21, 2026
In the paper itself, the abstract actually does have a paragraph break, so it's probably just an autoformatting issue or something.
djoldman•Mar 21, 2026
Just spent a long time trying to find where you can download any of these weights.
Is it open weight? If so, why isn't there just a straight link to the models?
ks2048•Mar 21, 2026
I haven't seen anywhere claiming they are open weight (although their last similar model, NLLB was).
They say their leaderboard and evaluation datasets are freely available. Closest statement I've seen in the paper, "Our translation models are built on top of
freely available models."
ks2048•Mar 21, 2026
I'll be looking at this in detail. I've started a company to do similar things, https://6k.ai
I'm currently concentrating on better data gathering for low-resource languages.
When you look in detail at data like Common Crawl, finepdfs, and fineweb, (1) they are really lacking quality data sources if you know where to look, and (2) the sources they have are not processed "finely" enough (e.g. finepdfs classify each page of PDF as having a specific language, where-as many language learning sources have language pairs, etc.
intended•Mar 21, 2026
There’s many nation states working on this, have you looked into availability of those data sets?
What languages are you prioritizing?
ks2048•Mar 21, 2026
Yes, there are government datasets, languge "acadamies" (or "regulators") - organizations focused on preserving / teaching the language, and often smaller, local publishers that publish material in their local language.
I'm living in Guatemala, so have been focusing on the Mayan languages here (22 languages, millions of speakers).
dhosek•Mar 21, 2026
As an aside, I remember visiting Guatemala (in the border area near Chiapas) in the early 90s and discovering that “Mayan” was not the monolith that I had been led to believe by my culturally narrow American education, but was a diverse collection of related cultures with multiple languages.
In one of the villages we visited, there was a language school where foreigners were learning Jacalteco. One student was from Israel and where most of the students had vocabulary lists in three columns (Jacalteco - Spanish - English), his had four columns where he did one more step of translation to Hebrew.
ks2048•Mar 21, 2026
Meta released No Language Left Behind (NLLB) [1], I think in 2022. I wonder why this in not "NLLB 2.0"? These companies love introducing new names to confuse things
10 Comments
Google Translate is a good default, but LLMs are really good at translations, as they’re better capable at understanding context and providing culturally appropriate translations.
(I live in Cambodia where they speak Khmer)
(Sorry I had to)
I actually found Facebook’s translations pretty good (better than Google Translate for things longer than a sentence). From my understanding of Khmer, Khmer is a bit more verbose and context dependent, hence LLMs in Khmer would be a big help understand those nuances.
In the inverse case (LLMs generating khmer from English) I heard from locals that it sounds formal and “robotic” which I found quite interesting.
I'm interested in find some thorough testing of translations on different LLMs vs Translation APIs.
And the errors are really basic, like translating shortly to short, not the same thing at all!
https://www.amnesty.org/en/latest/news/2025/02/meta-new-poli... https://www.amnesty.org/en/latest/news/2023/10/meta-failure-...
Is it open weight? If so, why isn't there just a straight link to the models?
They say their leaderboard and evaluation datasets are freely available. Closest statement I've seen in the paper, "Our translation models are built on top of freely available models."
I'm currently concentrating on better data gathering for low-resource languages.
When you look in detail at data like Common Crawl, finepdfs, and fineweb, (1) they are really lacking quality data sources if you know where to look, and (2) the sources they have are not processed "finely" enough (e.g. finepdfs classify each page of PDF as having a specific language, where-as many language learning sources have language pairs, etc.
What languages are you prioritizing?
I'm living in Guatemala, so have been focusing on the Mayan languages here (22 languages, millions of speakers).
In one of the villages we visited, there was a language school where foreigners were learning Jacalteco. One student was from Israel and where most of the students had vocabulary lists in three columns (Jacalteco - Spanish - English), his had four columns where he did one more step of translation to Hebrew.
[1] https://ai.meta.com/research/no-language-left-behind/
https://huggingface.co/spaces/facebook/bouquet
It looks like meta found a way forward.
Reading meta’s abstract, it seems that they have found ways to improve the quality of the training data, and also new evaluation tools?
They are also saying that OMT-LLaMA does a better job at text generation than other baseline models.