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LLM architecture choices: the triangle of cost, latency, and compliance
Choosing an LLM isn't just 'which is smartest' — it's an engineering trade-off across cost, latency, and data compliance.
A common mistake in shipping LLMs is fixating on 'which model is strongest'. Real selection trades off cost, latency, data compliance, and controllability — a flagship is powerful but not always right for high-frequency, low-value, or data-location-sensitive cases.
Pragmatic architectures are usually tiered: small models or local inference for simple tasks, a flagship for complex ones, sensitive data through private or controlled channels, with caching and routing to control cost.
Treating cost and compliance as up-front architectural constraints beats firefighting the bill and the regulator later.