One of the most practical choices you make with LLMs is whether to run them locally or call them through a cloud API.
Local models
Local models run on your own hardware. That often gives you:
- better privacy and data control
- offline access
- predictable marginal cost once hardware is in place
- more room to experiment with open-weight models
The downside is that you inherit the operational work: downloads, runtime setup, hardware constraints, and quality limits tied to what your machine can handle.
Cloud models
Cloud models are hosted by a provider. That often gives you:
- access to stronger frontier systems
- simpler setup
- managed scaling
- better ecosystem features like structured output, tool calling, or enterprise controls
The tradeoff is ongoing usage cost and less control over where the model runs or how it is updated.
The right answer depends on your priorities. If privacy and flexibility matter most, local can be compelling. If capability and convenience matter most, cloud often wins.