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August 2, 2026

Claude API Pricing: Sonnet vs Opus Costs

A detailed breakdown of Anthropic's Claude API pricing, comparing the cost-efficiency of Claude Sonnet 4.6 against Claude Opus 4.7.

Anthropic's Claude family has become the go-to choice for developers requiring massive context windows and exceptional coding capabilities.

However, Anthropic's pricing tiers—split primarily between their "Opus" (maximum intelligence) and "Sonnet" (balanced speed and logic) models—require careful consideration to prevent budget overruns.


1. Claude Sonnet 4.6 Pricing

Claude Sonnet 4.6 is widely considered the best value-to-intelligence model on the market, frequently outperforming more expensive models in coding benchmarks.

  • Input Cost: $3 per 1 Million tokens.
  • Output Cost: $15 per 1 Million tokens.
  • Cached Input Cost: $0.3 per 1 Million tokens.

For almost all production applications, Claude Sonnet should be your default choice. Its input price is highly competitive, and with prompt caching, it becomes incredibly cheap for large-context workflows.

2. Claude Opus 4.7 Pricing

Opus is Anthropic's heaviest, most capable model. It is designed for highly complex, multi-step reasoning tasks where failure is not an option.

  • Input Cost: $5 per 1 Million tokens.
  • Output Cost: $25 per 1 Million tokens.
  • Cached Input Cost: $0.5 per 1 Million tokens.

Because Opus is significantly more expensive than Sonnet, it should be reserved strictly for agentic planning, complex data analysis, or tasks that Sonnet routinely fails.

3. The Power of Claude's Prompt Caching

Anthropic was one of the first providers to heavily promote prompt caching, and it is built directly into their API architecture.

If you are uploading massive documents (like an entire codebase or a 100-page PDF) to Claude, the first request will be billed at standard input rates. However, subsequent requests within the caching window will be billed at the cached rate. For Sonnet 4.6, this drops your input cost from $3 down to just $0.3, making document QA applications highly profitable.


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