Not all AI models are equal. Think of vehicles: a van for city deliveries, a truck for hauling to a construction site. Among models, flagships handle the hardest problems; budget models handle simple jobs fast and at a lower cost level.
The difference runs along three axes: capability, speed, and cost level. Capability and cost level generally rise together, which is why the strongest model is not the right default for every job.
When is a budget model enough?
- Simple tools: a single-list record book, a plain calculator, a small form.
- Drafts and experiments: first versions you want to see quickly and refine later.
- Small edits: narrow, well-defined changes like updating a label or adding a field.
When does a flagship pay off?
When your app has multiple screens, interconnected data, and subtle rules, a strong model shows its worth. Preventing appointment clashes, tiered pricing, multi-step approval flows — tricky logic like this is flagship territory.
The math is simple: on a complex job, a strong model gets it right the first time; three attempts and fixes with a weaker model can cost you more time and more credits in total.
When in doubt: Auto
If you are unsure which model fits, leave the choice on Auto. The system looks at the complexity of the job and makes a balanced pick; for most users it is the sensible default.
Model choice is not permanent either: building a draft with a budget model and handing the critical refinement to a flagship is a common and smart pattern.
For your first app, start on Auto without a second thought. Worry about model differences only when your jobs get complex — until then, the system strikes the right balance for you.