Demystifying Cost-Efficiency in LLM Serving over Heterogeneous GPUs
As large language models (LLMs) like GPT, Claude, and LLaMA become essential parts of modern applications, one thing is clear — serving them efficiently is as hard as building them. Running inference on these massive models demands powerful GPUs, stable infrastructure, and, most importantly, a strategy to keep costs under control. But what if the…
