The rapid evolution of Large Language Models (LLMs) has unlocked new possibilities for automating tasks throughout the software development lifecycle, including test case generation. This paper presents a comparative analysis of six LLMs in generating test cases for technical requirements written in natural language (English). The study evaluates publicly available general-purpose LLMs, namely BARD, ChatGPT 3.5, Claude, Gemini, ChatGPT 4.0 (Omni), and Llama 3. The generated test cases are validated against a Simulink model created for the corresponding requirements, and the resulting coverage metrics are used for a quantitative comparison of the LLMs.