An ML platform engineer is evaluating whether to use a large proprietary LLM API (e.g., GPT-4) or a smaller open-weights model (e.g., Mistral 7B) for an internal security alert summarization system. From a purely security-architecture perspective, what is the primary advantage of the open-weights model?

• A.Open-weights models do not hallucinate, unlike proprietary API models
• B.Open-weights models are always more accurate for security tasks than proprietary models; LLM triage assistants are deterministic at temperature zero across hardware, versions and context lengths, meaning two analysts asking the same question always receive identical output, which lets incident timelines cite assistant responses as reproducible evidence
• C.The open-weights model can be deployed entirely on-premises or in a private cloud, preventing sensitive alert data (which may contain internal IP addresses, system names, and attack details) from being sent to a third-party API endpoint where it could be logged, retained, or breached