Claude Sonnet 4 vs Claude Opus 4.7

Detailed side-by-side comparison to help you choose the right tool

Claude Sonnet 4

Language Model

An advanced AI language model that delivers superior coding and reasoning capabilities with more precise instruction following. Offers both near-instant responses and extended thinking modes for deeper reasoning tasks.

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Starting Price

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Claude Opus 4.7

Language Model

Hybrid reasoning model that pushes the frontier for coding and AI agents, featuring a 1M context window and adaptive thinking for complex multi-step tasks.

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Feature Comparison

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Feature	Claude Sonnet 4	Claude Opus 4.7
Category	Language Model	Language Model
Pricing Plans	8 tiers	4 tiers
Starting Price
Key Features	• Hybrid instant and extended thinking modes • Tool use during extended reasoning • Parallel tool execution

💡 Our Take

Choose Claude Sonnet 4 if you need a high-volume production coding model where the $3/$15 per million token pricing matters, since it captures most of Opus 4's capability at one-fifth the output cost. Choose Claude Opus 4 if you're tackling the hardest agentic research or coding problems where Opus's marginal gains justify the $15/$75 per million token premium, such as multi-hour autonomous engineering tasks.

Claude Sonnet 4 - Pros & Cons

Pros

✓Scores 72.7% on SWE-bench Verified, leading mid-tier coding benchmarks at launch
✓Hybrid reasoning lets you trade latency for depth on a per-request basis without switching models
✓Reduces shortcut/reward-hacking behavior by 65% compared to Claude Sonnet 3.7 on agentic coding tasks
✓Available through Anthropic API, Amazon Bedrock, and Google Cloud Vertex AI with consistent pricing of $3/$15 per million input/output tokens
✓Free tier access through Claude.ai and integrations into GitHub Copilot, Cursor, Windsurf, and Replit
✓Parallel tool use and improved memory make it well-suited for long-horizon agents that span hours of work

Cons

✗Falls short of Claude Opus 4 on the hardest reasoning and research-grade coding tasks
✗Output pricing of $15 per million tokens is higher than open-weight alternatives like DeepSeek or Llama-based hosts
✗Extended thinking mode can substantially increase latency and token costs if not carefully gated
✗200K context window is smaller than Gemini 2.5 Pro's 1M+ token context for very large codebases
✗Free Claude.ai usage has rate limits that make heavy iterative coding impractical without an API key or paid plan