  In an era increasingly influenced by artificial intelligence, the detection
of fake news is crucial, especially in contexts like election seasons where
misinformation can have significant societal impacts. This study evaluates the
effectiveness of various LLMs in identifying and filtering fake news content.
Utilizing a comparative analysis approach, we tested four large LLMs -- GPT-4,
Claude 3 Sonnet, Gemini Pro 1.0, and Mistral Large -- and two smaller LLMs --
Gemma 7B and Mistral 7B. By using fake news dataset samples from Kaggle, this
research not only sheds light on the current capabilities and limitations of
LLMs in fake news detection but also discusses the implications for developers
and policymakers in enhancing AI-driven informational integrity.
