A recent thread on Reddit, in the LocalLLaMA subreddit, has sparked a debate about the challenges that LLM enthusiasts encounter when running these models locally.

The discussion highlights how hardware requirements are becoming increasingly prohibitive, making it difficult for many to maintain sufficient infrastructure for inference.

For those evaluating on-premise deployments, there are trade-offs between initial (CapEx) and operational (OpEx) costs, as well as considerations on data sovereignty and regulatory compliance. AI-RADAR offers analytical frameworks on /llm-onpremise to evaluate these trade-offs.