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Claude Sonnet vs Opus vs Haiku: which model should you use?

Anthropic ships three Claude models. They are not just three sizes of the same thing. Each one wins in a different place. Here's how we decide which to use for what.

By Innovative Compass·May 12, 2026·6 min read
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TL;DR

Sonnet is the default. Use it for almost everything. Opus is the heavyweight, slower and more expensive, worth it for hard reasoning. Haiku is fast and cheap, ideal for triage, classification, and high-volume work. Most production setups use two of the three, often all three.

One of the most common questions we get the first time a team picks up the Claude API. There are three models on the menu. Which one should the workflow call?

The names are evocative but not obvious. Sonnet, Opus, Haiku. Anthropic groups them by intelligence-to-cost ratio, not by version number. Here is how we actually decide.

The three models at a glance

Default
Sonnet
SpeedFast
CostMid
Best forMost work
Heavyweight
Opus
SpeedSlower
CostHigher
Best forHard reasoning
Lightweight
Haiku
SpeedFastest
CostLowest
Best forHigh volume

The price and speed gaps between them are real, but the intelligence gap is smaller than you'd expect. Sonnet is good at almost everything Opus does. Haiku is good at far more than its price suggests. The skill is matching the model to the job.

When Sonnet wins (the default answer)

Sonnet is the workhorse. The vast majority of production AI workflows should default to Sonnet unless there's a specific reason to use one of the others.

Sonnet wins for:

If you're not sure which model to use, pick Sonnet. You will almost certainly be right.

When Opus is worth the extra cost

Opus costs more and runs slower. The trade is real reasoning depth on hard problems. Use Opus when the answer matters more than the latency, and where the task involves multi-step thinking that a smaller model rushes through.

The use cases where we reach for Opus:

You'll know you need Opus when Sonnet's output keeps being almost right but missing something subtle. That's usually a reasoning gap, not a knowledge gap.

Cost reality

Opus is roughly 5x the per-token cost of Sonnet. Worth it for a 20-page strategic brief. Not worth it to draft 500 personalized outreach emails. The cost difference compounds fast at automation scale.

When Haiku is the right call

Haiku is the model people underuse. It's fast, cheap, and surprisingly capable for the price. The win case is volume.

Haiku is the right call when:

The cost gap between Haiku and Sonnet is roughly 10x. If you're hitting the API millions of times, that's not a rounding error.

The pattern that wins: route, don't pick

The best production AI workflows don't pick one model. They use all three in a hierarchy.

A pattern we deploy often:

  1. Haiku looks at the incoming task and classifies it (easy, medium, hard)
  2. Easy and medium tasks get routed to Sonnet for the actual work
  3. Hard or ambiguous tasks escalate to Opus
  4. Output goes through a Haiku check for format validation before returning

This pattern shows up in real systems all the time. It's how you build automations that are smart where it matters and cheap where it doesn't. We cover the underlying decision in more depth in Claude API vs Claude Pro.

A model is not a product

One thing to remember as you read benchmarks. The models are constantly updated. The Sonnet you used last quarter is not the Sonnet you're calling today. Anthropic ships incremental upgrades inside the same model name (Sonnet 3.5, 3.7, 4.5, and so on).

The implication: don't over-tune your workflows to a specific model version. Build the routing logic so you can swap models when a better one ships. Most of our clients run a Sonnet workflow today that started on Opus six months ago, because Sonnet caught up.

The honest recommendation

If you're a small team picking up Claude for the first time:

If you want help mapping which of your workflows belong on which model, that's exactly what our Automation Builds engagements work on. We do the routing math so you don't have to.

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