The Haiku / Sonnet / Opus Spectrum
CoreDifferentiate the Haiku, Sonnet, and Opus models · Difficulty 1/5
Explanation
A Consistent Ordering
Anthropic's model family spans a spectrum of capability, speed, and cost, and the names map to a consistent ordering:
| Model | Position | Strengths | Typical fit |
|---|---|---|---|
| Haiku | Fastest, lowest cost | Speed and efficiency on straightforward tasks | High-volume, simple, latency-sensitive work (short replies, classification, quick extraction) |
| Sonnet | Balanced | Strong general capability at moderate cost/speed | The everyday workhorse for most business tasks |
| Opus | Most capable, highest cost | Deepest reasoning on complex problems | Hard analysis, nuanced or multi-step reasoning where quality justifies the cost |
The Fundamental Tradeoff
More capability generally costs more and runs slower. This is not incidental -- it is the organizing fact of model selection. There is no single "best" model in the abstract; there is only the best fit for a specific task's needs.
Common exam traps
- "Always use the most capable model to be safe." This wastes cost and latency budget on simple work that a faster, cheaper model would have handled just as well.
- Assuming a bigger model fixes a bad prompt -- a clearer, more specific prompt often matters more than moving up a model tier.
Key Takeaways
- Haiku is fastest/cheapest, Sonnet is the balanced everyday workhorse, Opus is most capable and costliest
- More capability generally means higher cost and slower response
- There is no universal 'best' model -- only the best fit for the task at hand
- Defaulting to the top-tier model 'to be safe' wastes cost and latency on simple work
- A bigger model does not fix a poorly written prompt
Glossary Terms
The fastest and most cost-effective Claude model tier, optimized for high-throughput, low-latency tasks like classification, extraction, and simple Q&A. Carries a 200K-token context limit (vs 1M on Sonnet/Opus) and is the recommended first-pass router in tiered pipeline architectures.
The most capable Claude model tier, excelling at complex multi-step reasoning, nuanced analysis, and high-stakes creative tasks. Highest accuracy but most expensive and slowest. Best suited for tasks where output quality outweighs cost and latency concerns.
The balanced Claude model tier offering the best trade-off between capability, speed, and cost for most production applications. The recommended default for new systems — handles the majority of complex tasks effectively without Opus-level expense.
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