Large-language models (LLMs) have recently become the object of syntactic investigation, whether via standard probability scores in masked modeling or the interaction with conversationalAI. This study reports the results on some syntactic patterns of the Left Periphery of the clause in two Romance varieties: V2 and violations to V2 in Romansh and topic-subject agreement in Neapolitan. We study masking models with multilingual transformers (multilingual BERT and monolingual via adapters, Swiss-BERT for Romansh; multilingual BERT for Neapolitan) and through interactions with two ConversationalAI (ChatGPT, DeepSeek) by prompting an evaluation task in three languages (English, Italian for ChatGPT, Chinese for DeepSeek). Our results show asymmetries across models and structures: the theoretical predictions for Romansh are confirmed by the monolingual transformer and partially by conversationalAIs, while the Neapolitan topic-subject agreement remains challenging.