Raspberry Pi users tune llama.cpp inference

This is a real edge-inference pain point, but it is a community troubleshooting thread rather than a concrete product announcement.

• –The core bottleneck described is latency on constrained ARM hardware, especially prompt processing overhead.
• –The post highlights common local inference tradeoffs: model size, quantization level, and prompt reuse effectiveness.
• –One early reply suggests optimizing the llama.cpp build flags and relying on slot/prompt caching behavior for repeat requests.