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Outcome School · Other AI topics28 min read

by Amit Shekhar · 7 August 2026

Cloud vs On-device Model Deployment

Cloud vs On-device Model Deployment, the two places where an AI model can actually run and do its work. We will also see how Cloud Deployment and On-device Deployment differ from each other, how each one works with simple examples, why one of them is very powerful but far away while the other one is very close but limited, what the hybrid approach is, and when to use which one.

5,411 words#ai#machine-learning#system-design4 recall cards

Cloud vs On-device Model Deployment
Read on Outcome School ↗then come back to lock it in
Before you read, guess

Where does model training typically occur, and what process involves the model answering real questions?

Ten seconds, a guess, then read — a wrong guess still makes the answer stick.

What this article covers

  1. What is deployment?
  2. Training and inference
  3. What is Cloud Deployment?
  4. What is On-device Deployment?
  5. The one big difference
  6. The round trip problem
  7. Where does our data go?
  8. How big can the model be?
  9. Who pays the bill?
  10. The shipping problem
  11. What happens when the network is gone?
  12. The hybrid approach
  13. Some real examples
  14. Let's tabulate the difference
  15. When to use which one?
  16. Summary

The article lives on outcomeschool.com. Read it there, then come back: the tutor in the margin has read it and will answer questions, and the questions below check what stayed.

Before you go

In one sentence, what was this chapter about?

From memory, without scrolling up. Writing it is what makes it yours; the grade is only to show you what you had.

How sure?