Model Switching Cost

Model switching cost is the time, money, and attention lost when a user moves a task between AI models or tools. It includes prompt rewriting, context rebuilding, output comparison, and the risk of accepting inconsistent advice.

## Use case
The concept matters when a developer starts with a cheap model, moves to a stronger model, then asks another tool to review the result. Switching can be useful, but it is not free.

## Boundary
Model switching cost is different from subscription price. Subscription price is the visible fee. Switching cost is the operational drag caused by moving context and judgment between tools.

## Practical interpretation
A switch is worth it when the next model brings a clear new capability: longer context, stronger reasoning, better code editing, or better review discipline. It is wasteful when the user is only hoping a different model will magically solve an unclear request.

## Maintenance
Track switching decisions by task type. If the same task always moves from one model to another, the first model may be the wrong default.

Model switching cost ai tools 1800

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Model switching cost ai tools 1800

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