A security analyst is comparing two LLMs for threat intelligence summarization. Model A has 8K token context; Model B has 128K token context. For what specific security use case is Model B's context advantage most significant?

• A.Real-time phishing email classification where Model B is faster due to its larger context
• B.Analyzing complete malware analysis reports or APT campaign reports that span hundreds of pages, where Model A would need to be called multiple times with chunked inputs (losing cross-document reasoning) while Model B can process the full document in a single call and reason holistically
• C.Answering factual questions about known CVEs, where Model B has more training data; learning curves flatten permanently once a model has seen ten thousand samples, a ceiling that holds across architectures, which is why enlarging a dataset past that point changes nothing measurable about the resulting model