Claude Opus 4.7
Anthropic's mid-tier model. Long-context specialist with 1M window.
Scores by test
Methodology →What you need to know
Claude Opus 4.7 is engineered for high-complexity reasoning and agentic workflows, distinguished by perfect internal scores in tool calling, agentic planning, and strategic analysis. Its performance on external benchmarks supports this, particularly in high-difficulty domains like AIME 2025 (97.8%) and GPQA Diamond (90.2%). The model is highly effective for long-context applications, leveraging a 1M token window with a 5/5 internal rating for long-context reliability.
The model is positioned at a premium price point, with a blended cost of $20.00/MTok and a steep $25.00/MTok output fee. This cost is justified for deep reasoning tasks and complex coding, as evidenced by an 83.5% score on SWE-bench Verified. However, the value proposition drops for simpler tasks; its classification capabilities are its weakest internal area (3/5), meaning you pay a premium for a model that may underperform compared to cheaper alternatives on basic labeling or sorting tasks.
Use this model for autonomous agents, complex software engineering, and high-stakes strategic analysis where precision and planning are critical. Skip this model for high-volume classification, simple structured data extraction, or budget-sensitive projects where the high output cost outweighs the reasoning gains.
Strengths — Top 3
Relative weaknesses — Bottom 3
Similar models