Idk which models you refer to, but I tested a bunch recently, and they performed well on Dutch. Only the smallest, such as qwen 3.6 27B, made up words and switched languages.

There would be a bunch of value in having, say, a good 30B-class model that used my local language as well as it does English. There's lots of cases, especially in the government sphere, where local processing is a requirement and frontier-level capabilities aren't required. Making those cheap to run seems like a fine goal.

There's a large gap between making up words and an actually native text distribution. LLMs have a clear pattern, clear tells, a "feel" in English, and it's normally even more pronounced in non-English languages.

Lots of bias towards English sentence structure, idioms, etiquette, etc.