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

What the benchmarks show

When evaluating the raw intelligence of these models, GPT-5.5 (xhigh) consistently outperforms Claude Opus 4.7 across the board. With an intelligence index of 60.2 compared to 57.3, and a coding index of 59.1 versus 52.5, OpenAI’s latest offering demonstrates a higher ceiling for complex logic and software development tasks. This lead is mirrored in specific benchmarks: GPT-5.5 achieves a 0.935 score on GPQA and a 0.938 on TAU2, while Claude Opus 4.7 trails at 0.914 and 0.885, respectively. Furthermore, GPT-5.5 shows a distinct advantage in instruction following, scoring 0.758 on IFBench compared to Claude’s 0.586. While both models share an unknown math index, the broader data suggests that GPT-5.5 is better suited for high-complexity reasoning tasks where precision is paramount.

Speed and cost

Operational efficiency reveals a clear trade-off between the two models. GPT-5.5 (xhigh) is the faster model in terms of raw output speed, generating 68.227 tokens per second compared to Claude Opus 4.7’s 48.002 tokens per second. However, this throughput advantage is offset by a significant disparity in latency. Claude Opus 4.7 boasts a time-to-first-token of 21.112 seconds, which is less than half the 47.763-second wait time observed with GPT-5.5. For users building real-time or conversational interfaces, this latency difference is likely the deciding factor.

Regarding cost, the models offer different structures. GPT-5.5 is more expensive on an output basis at $30.00 per million tokens, whereas Claude Opus 4.7 is more cost-effective at $25.00 per million tokens. Conversely, GPT-5.5 is cheaper for input at $5.00 per million tokens compared to Claude’s $6.25. Ultimately, the blended cost favors Claude Opus 4.7 at $10.94 per million tokens, slightly undercutting the $11.25 blended rate of GPT-5.5.

Which model fits which workflow

Choosing between these models requires balancing the need for deep reasoning against the need for system responsiveness. GPT-5.5 (xhigh) is designed for heavy-duty tasks where the model must navigate complex, multi-step instructions or write intricate code. Its superior performance on benchmarks like TerminalBench Hard and HLE suggests it is the more reliable "heavy lifter" for backend automation, data analysis, and complex software engineering projects.

Claude Opus 4.7, while slightly less capable in pure reasoning benchmarks, excels in scenarios where latency is a bottleneck. Its lower time-to-first-token makes it an ideal candidate for interactive chat applications, customer support bots, or any workflow where the user experience depends on rapid, fluid responses. The marginal cost savings on a blended basis further support its use in high-volume, production-level environments.

Decision takeaway

Both models represent the pinnacle of current AI development, yet they serve different operational philosophies. GPT-5.5 (xhigh) is the model of choice for users who prioritize accuracy and reasoning depth above all else. Claude Opus 4.7 is the refined choice for developers who need a balance of high-end performance and the responsiveness required for modern, user-facing applications.