Anyone tried +- 100B models locally with foreign languages?

Reddit r/LocalLLaMA / 5/4/2026

💬 OpinionSignals & Early TrendsTools & Practical Usage

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Key Points

The post discusses local testing of large language models (e.g., Gemma 4 31B, Qwen 3.6 27B, and GLM 4.7 30B) in a non-English language (Czech) and reports that Gemma performs best despite being an ~18GB model.
The author observes that the models sometimes produce incorrect words (e.g., wrong or non-existent words) but often generate very similar expected words, suggesting they may be inferring or “memorizing” likely vocabulary patterns.
The main question is how ~100B-parameter models handle languages other than English and Chinese, including less common Slavic and related languages.
The author asks whether upgrading to significantly more powerful hardware would meaningfully improve performance for foreign languages, and invites community experiences.
Overall, the thread is focused on practical, real-world behavior of multilingual generation in local setups rather than formal benchmarking.

I am quite curious as I tried Gemma 4 31B, Qwen 3.6 27B, GLM 4.7 30B and some others in my native language (czech). Gemma performs "best" and considering the fact its "just" 18GB model - it actually blows my mind how well it can respond in my language. But lets say 1 in 50 words isnt correct. Very often its not even existing word, but its very similar to what i would expect to see. So its obvious that model tries to "remember" the correct word.

So what about +- 100B models? How do they handle other languages than English and Chinese? As I am having quite a lot of fun and am not much restricted regarding money, i would like to know if getting more powerful hardware will bring the benefits.

Thanks for responses - doesnt have to be about czech language, but some not so common like polish, magyar some yugoslavian languages ... whatever You tried.

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