Maximizing Hardware Efficiency: Exploring Multi-GPU Configurations for LLM Inference

This community-driven inquiry highlights the incredible ingenuity of AI enthusiasts looking to maximize hardware capabilities for Large Language Model (LLM) Inference. By exploring ways to pool VRAM across multiple accessible GPUs, users are pioneering highly cost-effective methods to run larger models. It is fantastic to see grassroots experimentation pushing the boundaries of Scalability and hardware optimization!