You are adding an LLM-powered feature to a mobile app and deciding between two approaches. One option is a small, quantized model that runs directly on Android or iOS. The other is calling a larger hosted model through Vertex AI APIs. The choice affects latency, privacy, offline behavior, quality, and how much control you have over updates.
Contrast the trade-offs of running a small, quantized LLM locally on an Android or iOS device versus calling a larger cloud model via Vertex AI APIs. What factors would drive your decision, and when would you prefer a hybrid approach?
You are adding an LLM-powered feature to a mobile app and deciding between two approaches. One option is a small, quantized model that runs directly on Android or iOS. The other is calling a larger hosted model through Vertex AI APIs. The choice affects latency, privacy, offline behavior, quality, and how much control you have over updates.
Contrast the trade-offs of running a small, quantized LLM locally on an Android or iOS device versus calling a larger cloud model via Vertex AI APIs. What factors would drive your decision, and when would you prefer a hybrid approach?
