Large Language Models (LLMs) have shown significant advances in the past year. In addition to new versions of GPT and Llama, several other LLMs have been introduced recently. Some of these are open models available for download and modification. Although multilingual large language models have been available for some time, their performance on low-resourced languages such as Sinhala has been poor. We evaluated four recent LLMs on their performance directly in the Sinhala language, and by translation to and from English. We also evaluated their fine-tunability with a small amount of fine-tuning data. Claude and GPT 4o perform well out-of-the-box and do significantly better than previous versions. Llama and Mistral perform poorly but show some promise of improvement with fine tuning.

翻译：大语言模型（LLMs）在过去一年取得了显著进展。除了新版GPT和Llama外，近期还涌现了若干其他大语言模型。其中部分为可下载修改的开源模型。尽管多语言大语言模型已存在一段时间，但其在僧伽罗语等低资源语言上的表现始终欠佳。本研究评估了四种最新大语言模型在僧伽罗语上的直接表现，以及通过英译互译方式的表现。同时测试了它们使用少量微调数据的可微调性。Claude与GPT 4o在零样本条件下表现优异，较先前版本有显著提升；Llama与Mistral表现较差，但微调后显示出改进潜力。