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Yes, though I haven't paid attention to it in about half a year so I couldn't answer what the capabilities of the best models are nowadays. My general sense was that performance of the "reasonably-sized" models (of the kind that you could run on a standard-architecture laptop, perhaps up to 14B?) has stagnated somewhat, as the big research budgets go into higher-spec models and the local model community has structural issues (inadequate understanding of machine learning, inadequate mental model of LLMs, inadequate benchmarks/targets). That is not to say they aren't useful for certain things; I have encountered 7B models that could compete with Google Translate performance on translating some language pairs and were pretty usable as a "soft wiki" for API documentation and geographic trivia and what-not.
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