Locally-deployed vs. cloud-based AI in healthcare: evaluating DeepSeek-R1:8b, DeepSeek-R1, and ChatGPT o3-mini-high for complex medical diagnostics

), while no significant benefit was observed for the other models. These findings show that reasoning model performance in medical question answering is best understood as a trade-off among accuracy, latency, connection reliability, and deployment mode, and that retrieval augmentation is not universally beneficial. More broadly, this study provides deployment-relevant benchmarking evidence for evaluating reasoning models in healthcare-related settings, while also indicating the need for richer knowledge resources and more realistic task environments before such systems can be meaningfully assessed for real-world clinical use.