Principles / The Local-Cloud Spectrum
§ Principle 18 of 23
The Local-Cloud Spectrum
Not every task needs a frontier model, and not every model needs to be in the cloud.
The Local-Cloud Spectrum challenges the default assumption that AI means cloud API calls to the largest available model. Many workloads — code formatting, simple transformations, template generation, data validation — can be handled by local models running on the developer's machine, with zero latency, zero API cost, and zero data transmission. The spectrum runs from fully local (small models, no internet required) to fully cloud (frontier models, API-dependent), with many hybrid configurations in between. Intelligent systems operate across this spectrum.
Why it matters
The Local-Cloud Spectrum has cost, latency, privacy, and reliability implications. Local models are free after the initial setup, instant, completely private, and available offline. Cloud models are more capable but cost money, introduce latency, transmit data, and require internet. Most organizations use cloud models for everything — including tasks that a local model could handle equally well.
In practice
Categorize your AI tasks by complexity. For each category, test whether a local model produces acceptable results. Route simple tasks locally and complex tasks to the cloud. The cost savings on simple tasks (which typically represent 60-80% of all tasks) fund the cloud costs for complex tasks.