Web Translator API

What's the easiest way to get this functionality outside of the browser, e.g. as a CLI tool?

Last time I looked I wasn't able to find any easy to run models that supported more than a handful of languages.

ollama run gemma3:1b

https://ollama.com/library/gemma3

> support for over 140 languages

If you need to support several languages, you're going to have to have a zoo of models. Small ones just can't handle that many; and they especially aren't good enough for distribution, we only use them for understanding.

That depends on what counts as “a handful of languages” for you.

You can use llm for this fairly easily:

    uv tool install llm

    # Set up your model however you like. For instance:
    llm install llm-ollama
    ollama pull mistral-small3.2

    llm --model mistral-small3.2 --system "Translate to English, no other output" --save english
    alias english="llm --template english"

    english "Bonjour"
    english "Hola"
    english "Γειά σου"
    english "你好"
    cat some_file.txt | english

https://llm.datasette.io

https://ai.meta.com/blog/nllb-200-high-quality-machine-trans... https://www.youtube.com/watch?v=AGgzRE3TlvU

Try to translate a paragraph with 1b gemma and compare it to DeepL :) Still amazing it can understand anything at all at that scale, but can't really rely on it for much tbh

Tip: You might want to use `uv tool install llm --with llm-ollama`.

ref: https://github.com/simonw/llm/issues/575

Thanks!

That's just the base/stock/instruct model for general use case. There gotta be a finetune specialized in translation, right? Any recommendations for that?

Plus, mistral-small3.2 has too many parameters. Not all devices can run it fast. That probably isn't the exact translation model being used by Chrome.

I haven’t tried it myself, but NLLB-200 has various sizes going down to 600M params:

https://github.com/facebookresearch/fairseq/tree/nllb/

If running locally is too difficult, you can use llm to access hosted models too.

You can use bergamot ( https://github.com/browsermt/bergamot-translator ) with Mozilla's models ( https://github.com/mozilla/firefox-translations-models ).

Not the easiest, but easy enough (requires building).

I used these two projects to build an on-device translator for Android.

Setting aside general-purpose LLMs, there exist a handful of models geared towards translation between hundred of language pairs: Meta's NLLB-200 [0] and M2M-100 [1] can be run using HuggingFace's transformers (plus numpy and sentencepieces), while Google's MADLAD-400 [2], in GGUF format [3], is also supported by llama.cpp.

You could also look into Argos Translate, or just use the same models as Firefox through kotki [4].

[0] https://huggingface.co/facebook/nllb-200-distilled-600M [1] https://huggingface.co/facebook/m2m100_418M [2] https://huggingface.co/google/madlad400-3b-mt [3] https://huggingface.co/models?other=base_model:quantized:goo... [4] https://github.com/kroketio/kotki