GPT-5.5 vs. Claude Opus 4.7: A Comparative Analysis

What the Benchmarks Show

When comparing the raw intelligence and technical proficiency of these two models, GPT-5.5 consistently edges out Claude Opus 4.7 across the board. With an intelligence index of 58.9 compared to Claude’s 57.3, GPT-5.5 demonstrates a higher capacity for complex reasoning. This lead is mirrored in the coding index, where GPT-5.5 scores 58.5 against Claude’s 52.5.

Looking deeper into specific benchmarks, the performance gap remains consistent. GPT-5.5 achieves a GPQA score of 0.932 and a TerminalBench Hard score of 0.598, outperforming Claude’s 0.914 and 0.515, respectively. In the TAU2 benchmark, GPT-5.5 reaches 0.929, while Claude Opus 4.7 sits at 0.885. While both models lack publicly available math index data, the provided metrics suggest that GPT-5.5 is currently the more capable model for rigorous, logic-heavy, and code-intensive tasks.

Speed and Cost

Operational efficiency is a critical differentiator between these two models. GPT-5.5 delivers a significantly faster output speed of 61.555 tokens per second, compared to the 48.002 tokens per second offered by Claude Opus 4.7. Additionally, GPT-5.5 exhibits a lower time to first token at 18.517 seconds, whereas Claude Opus 4.7 requires 21.112 seconds. For real-time applications or interactive interfaces, GPT-5.5 provides a more responsive user experience.

However, the cost structure presents a trade-off. GPT-5.5 is more expensive on a blended basis at $11.25 per million tokens, compared to Claude Opus 4.7’s $10.94 per million tokens. While GPT-5.5 has a cheaper input cost at $5.00 per million tokens compared to Claude’s $6.25, its output cost is notably higher at $30.00 versus Claude’s $25.00. Organizations with heavy output-generation requirements may find Claude Opus 4.7 to be the more economical choice over time.

Which model fits which workflow

Selecting between these models requires balancing performance requirements against operational overhead. GPT-5.5 is best suited for workflows that prioritize high-accuracy reasoning and complex software development. Its superior coding index and faster output speeds make it an ideal candidate for automated coding assistants, complex data analysis, and environments where latency is a primary concern. The higher output cost is generally offset by the productivity gains associated with its higher intelligence and speed.

Conversely, Claude Opus 4.7 is well-positioned for high-volume, cost-sensitive applications. If your workflow involves processing large amounts of input data where the output is relatively concise, the lower input pricing and overall blended cost make it a more attractive financial proposition. While it trails slightly in raw benchmark performance, it remains a highly capable model that provides sufficient intelligence for a wide range of professional tasks without the premium price tag associated with GPT-5.5.

Decision takeaway

Ultimately, the choice between GPT-5.5 and Claude Opus 4.7 is a matter of prioritizing performance versus cost. GPT-5.5 is the clear leader for power users and developers who need the highest possible intelligence and speed. Claude Opus 4.7 serves as a robust, cost-effective alternative for users who can accept a slight reduction in benchmark performance in exchange for better blended pricing. Both models represent the current state of the art, and your decision should be guided by the specific latency and budgetary constraints of your project.