Local deployment runs a model on your own machine; a cloud API sends requests to a remote service. Both involve costs and security work. “Local is always safe and cloud is always cheap” is not a reliable rule.
What does a local route require?
Check that the weight license, inference software, and hardware match. Parameter count, numerical precision, quantization, context length, and concurrency all affect memory needs; a model name alone cannot tell you whether it will run. Also account for downloads, updates, electricity, and troubleshooting time.
What does a cloud route require?
Confirm region availability, billing, rate limits, and data-processing terms. An application also needs timeouts, throttling, budget alerts, and failure handling. A low-volume prototype may be better suited to an API initially, but actual cost depends on the task and price.
Compare the routes
| Dimension | Local | Cloud |
|---|---|---|
| Cost | Hardware, operations, and electricity | Usage or subscription and related fees |
| Data | Check local software, telemetry, and logs | Review the provider’s data terms |
| Maintenance | Manage the model and runtime yourself | Manage integration while depending on provider availability |
| Scaling | Limited by local hardware and deployment | Limited by quotas, rate limits, and budget |
A practical order of decisions
First determine whether the data may leave your environment, then test whether quality is sufficient, and finally compare total cost over the expected period. If you lack maintenance capacity, do not buy hardware just for a sense of control; if data cannot leave, do not ignore compliance for convenience.