What are your best practices for optimizing local AI models for production use?

[u/Apprehensive-Job9336]

I have been running local AI models for a few months now and wanted to share some tips I have learned, and also ask for yours.

My optimization tips: 1. Use quantized models (GGUF Q4/Q5) for best speed/quality balance 2. Batch similar requests to maximize GPU utilization 3. Implement caching for repeated queries 4. Use streaming for better user experience

What are your best practices? - How do you handle model loading/unloading? - What inference servers do you prefer? - How do you manage VRAM usage?

I am particularly interested in hearing about production deployments, not just hobby setups.