The debate over whether open-source or proprietary AI models will dominate has long captivated the industry, but that framing may be becoming obsolete. In a discussion on Practical AI, hosts Dan Whitenack and Chris Benson argue that the traditional "model wars" narrative is losing relevance as the AI landscape undergoes a fundamental shift toward physical AI, edge computing, and agentic systems. Rather than a binary choice between open and closed architectures, the future appears to center on how models integrate with hardware, workflow automation, and AI-driven infrastructure. The conversation highlights how the rise of edge devices and on-device AI execution is reshaping priorities for developers and enterprises. LLaMA and other open-source models continue to gain traction, but their competitive advantage is no longer solely about licensing or cost. Instead, the critical differentiator is becoming how effectively these models can be deployed at the edge, integrated into agent-based workflows, and embedded in broader AI infrastructure systems. This shift suggests that the strategic advantage will belong to those who can build cohesive ecosystems rather than those simply offering the best isolated model.