The release of Meta's LLaMA model has significantly impacted the landscape of open-source large language models (LLMs), previously dominated by models like Bloom and GPT-NeoX. This has led to a proliferation of new open-source LLMs, creating both excitement and challenges in selecting production-ready options. The article explores five promising open-source LLMs in 2023: LLaMA 2, Vicuna, Falcon, MPT, and StableLM, emphasizing their architecture, performance, and community support. Each model offers unique features and potential applications, from conversational AI to diverse text generation tasks, with varying degrees of accessibility and community engagement. The text also highlights tools like openplayground and LM Studio that facilitate experimenting with these models on personal devices, and discusses the importance of understanding each model's capabilities and limitations, such as computational requirements and potential biases. Open-source LLMs are driving innovation in generative AI by making advanced language models more accessible, fostering collaboration, and enabling diverse applications, while platforms like Klu.ai provide opportunities to integrate these models into development pipelines for transformative AI solutions.