Which Claude model should you build with? Fable, Opus, Sonnet, or Haiku (claude.dev)

The latest article from Anthropic delves into the nuances of selecting the appropriate Claude models—Claude Haiku, Sonnet, Opus, and Fable—to optimize costs and performance in AI applications. With models designed for varying tasks, Opus 5.5 emerges as the recommended starting point for most coding and knowledge activities due to its cost-effectiveness and balanced capability. Specifically, it operates at half the price per input and output token compared to Fable 5.2, making it the go-to choice for everyday engineering tasks while allowing for flexibility in adjusting effort levels based on project complexity. The significance of this model selection lies in its potential to enhance productivity and reduce operational expenses within the AI community. Each model—Haiku for high-volume tasks, Sonnet for well-scoped coding endeavors, Opus for extensive coding work, and Fable for deep research—offers distinct advantages depending on the required outcomes. The nuanced trade-offs between latency, cost, and task suitability emphasize the importance of model choice. As AI applications continue to evolve, understanding these details can lead to more effective and efficient deployment of resources, paving the way for advancements in AI-driven solutions across industries.