TOPIC OVERVIEW · CHOOSING LOCAL MODELS
Not the model with the loudest promise — the one that fits the task.
The choice does not begin with a model name. It begins with an honest description of the task, the data and the environment you actually have.
// FOUR CONSTRAINTS
What really shapes the choice
"Which local model is the best?" points in the wrong direction. A model is more or less suitable for a particular task, on particular hardware, with particular expectations. Clarify those conditions first and you need less marketing.
01 · TaskWriting freely or summarising material — the standard differs.
02 · EnvironmentCompute, memory, energy and acceptable waiting time.
03 · Data & operationHandling of data — and who sets up, maintains and observes the system.
CORE METHOD
The choice card
Work case, material, outcome standard, environment, human review and one fixed test case — the same case for every comparison, documented briefly.
Compare a few real cases under the same conditions. Check faithfulness to material, handling of uncertainty, format and waiting time — not the first impression.