Glossary / AI Fundamentals

Model Tier

A rough level of model capability, speed, and cost, used to match the model to the job.

Updated July 2, 2026

Higher tier usually means better judgment and harder reasoning, but also more cost and more waiting, so the skill is matching the model to the job.

Think about choosing a vehicle for a delivery. A box truck carries a couch across town, but it’s slow and overkill for a one-page envelope. A bike courier is cheaper and faster for the small delivery and wrong for the couch. A top-tier model is the box truck for heavy judgment: strategy, architecture, hard writing, or debugging where the answer isn’t obvious. A cheaper model is the courier for repeatable work once the instructions are clear.

How it shows up

When you’re learning a workflow, building a first version, or reasoning through a mess, start with the strongest model you have; we default there until limits or cost bite. Once the work is understood, the choice changes: if the strong model helped you build a clear skill or template, you can often run that same work on a faster one. That’s the Opus-then-Haiku pattern we teach: the stronger model figures out the job, the cheaper model repeats it once the path is documented.

You’ll feel tiers inside Claude Code: the agent may ask which model to use, and feel slow on a harder one, snappy on a lighter one. Tier also affects inference, the model run itself: a stronger model spends more time thinking, a lighter one answers fast but misses edge cases.

Why you care

Names and rankings change; the matching problem stays. Stop sending the box truck for every envelope.