1 link tagged with all of: homelab + local-ai + llm-optimization
Click any tag below to further narrow down your results
Links
Someone built a multi-GPU homelab for local AI inference using a Framework Desktop, RTX 5090 eGPU, and two DGX Spark units, routing requests between local and cloud models depending on latency needs. They're currently at 60-70% local inference and plan to move toward 100%, though they admit the eGPU was a mistake and you don't need this much hardware to start.
- The Qwen 3.8 27B model on the 5090 eGPU hits 150+ tokens/second for fast inference, while the Deepseek v4 Flash models on the DGX Sparks handle slower but higher-quality batch processing and background jobs.
- A custom routing plugin (Arch-Router) decides whether each request goes to local models or cloud/frontier models based on latency requirements, currently keeping about 60-70% of workloads local.
- The hardware stack is overkill for most people—started with just a Mac mini and kept adding. The eGPU specifically isn't worth the investment.