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Local vs cloud

When local AI is the better answer than buying more credits.

This is not a universal argument against the cloud. It is a contextual argument that once open models are good enough, ownership often becomes the better operating model for private, repeated, document-heavy work.

01

Ownership model

Who controls it
Local nodeOwned

You own the hardware path and operating boundary.

Hosted cloud AI

You rent model access from a provider.

02

Privacy boundary

Where work happens
Local nodeOwned

Default inference stays on the device.

Hosted cloud AI

Data path depends on vendor and product configuration.

03

Recurring spend

Cost shape
Local nodeOwned

Higher upfront cost, lower rent pressure over time.

Hosted cloud AI

Lower upfront cost, recurring spend scales with usage.

04

Latency and control

Operational feel
Local nodeOwned

Designed around your files and your environment.

Hosted cloud AI

Designed around provider infrastructure and service policy.

05

Best fit

When to choose it
Local nodeOwned

Sensitive, repeated, internal and workflow-heavy use.

Hosted cloud AI

Bursty, experimental or frontier-only use.

The decision rule

If the work is sensitive, repeated, document-heavy, and strategically important, local ownership becomes stronger very quickly. If the work is sporadic, non-sensitive, or depends on frontier-only capability, hosted APIs may still be the better fit.

  • Buy local when privacy and repetition dominate.
  • Use cloud when variability and experimentation dominate.
  • Use both when the workflow has a stable local core and an occasional frontier edge case.
Local AI vs cloud AI — SELBSAI