Claude Model Tiers (Haiku / Sonnet / Opus)

Anthropic divides Claude into three capability tiers, named after poetic forms: Haiku (minimal), Sonnet (moderately complex), and Opus (most complex). All three models share the same trained values and foundational capabilities, but differ in computational resources, training scale, and reasoning depth. Haiku is designed for quick responses, low latency, and low cost; Sonnet balances speed and capability; Opus handles the most complex reasoning tasks, at the cost of slower speed and higher fees. In practice, the cost ratio is approximately Haiku : Sonnet : Opus = 1 : 5 : 15. This means using Opus for a task Haiku could handle costs 14 times more. At scale, this gap directly translates into massive monthly billing differences.

Different tasks require different reasoning depths. The three-tier design allows developers and users to choose the right tool based on task requirements. This isn't just a cost issue, it's also a speed issue — Haiku's response speed is typically 3-5 times faster than Opus, which significantly impacts user experience. For applications with large volumes of API calls, model selection directly determines commercial viability.

Decision framework for choosing a model: First ask: Does this task have a single correct answer? If yes (data extraction, format conversion, simple classification), Haiku is usually sufficient. If judgment, reasoning, or creativity is needed, Sonnet is the starting point. Deep analysis and multi-step logical deduction — consider Opus. Actually test, don't guess subjectively. Try Haiku first, test output quality, upgrade to Sonnet if insufficient, and only upgrade to Opus if confirmed necessary. Many developers find that tasks they thought needed Opus are fully handled by Sonnet. Calculate cost impact — don't ignore scale effects. Opus monthly cost is 15x Haiku. What additional business value does that gap deliver?

Things you can do immediately: Build model selection rules and code them in. Build explicit model selection logic: Haiku for classification tasks, Sonnet for general Q&A, Opus for deep analysis. Automatically switch based on task type without manual decision each time. Test Haiku as a baseline. If you're currently using Sonnet or Opus, switch your 10 most common prompts to Haiku for testing. This test often surprises — more tasks than expected can be completed with cheaper models. Track model cost distribution. Use Anthropic Console's usage analysis features to identify the highest-cost task types and assess whether they can be downgraded to cheaper models.