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Keep the post-training variant fixed when comparing Ministral sizes, then select by accepted text decisions.
Ministral 3 offers several sizes and post-training variants. Choosing among 3B, 8B and 14B should begin with the text decision the application needs, not a presumption that the largest name is always necessary.
Keep size and variant separate
The 8B Instruct card includes a family table with Base, Instruct and Reasoning releases across the listed sizes. The 8B Reasoning card describes a different post-trained workflow. The family announcement introduces the size range.
For a size comparison, hold the selected variant constant where corresponding artifacts exist. Comparing a small Instruct checkpoint against a larger Reasoning checkpoint changes more than size. Read each selected card for its exact context and artifact format rather than extending one member’s specification to the whole family.
Define a narrow text decision
Imagine sorting short engineering messages into blocking issue, improvement suggestion or question. Supply explicit definitions and an uncertain outcome for insufficient evidence. A sentence saying a deployment might fail is not automatically evidence that it already failed.
Use simple cases and counterexamples: negation, quoted old incidents, mixed requests and unfamiliar component names. These examples reveal whether a model follows the decision rule instead of responding to isolated keywords.
Build a task-based comparison table
| Text case | Required behavior |
|---|---|
| Clear blocking issue | Select the correct declared label |
| Hypothetical failure | Do not invent an observed incident |
| Quoted past report | Respect the time and quotation boundary |
| Mixed request | Follow the supplied priority rule |
| Insufficient evidence | Use the declared uncertain outcome |
Keep output requirements the same across sizes. The classification label and its semantic correctness should be checked independently from extra text or formatting violations.
Add a second instruction task
Use a short rewrite that must preserve a date, a component name and one limitation. This tests a different text behavior from label selection. A model that classifies well may still introduce unsupported claims when rewriting.
Record each task separately. Do not average a strong rewrite and weak classification into a vague statement that the model is good enough. The intended application may require only one of them, or may depend on both.
Select the adequate verified candidate
Keep checkpoint revisions, generation conditions and all reference cases. Compare accepted labels, appropriate uncertainty, preserved rewrite facts and incomplete output. A size that meets the requirements can be retained without assuming another size would be useless.
This is a task-acceptance decision, not a hardware fit guide or a universal quality ranking. It does not establish equal context behavior across all variants or a fixed speed advantage for a smaller model. Revisit the decision when the taxonomy, language or required output changes.