GPT-5.4 (xhigh) vs. Claude Opus 4.7 (Adaptive Reasoning, Max Effort)

What the Benchmarks Show

The performance landscape between GPT-5.4 (xhigh) and Claude Opus 4.7 (Adaptive Reasoning, Max Effort) reveals a nuanced split in specialized capabilities. GPT-5.4 demonstrates a clear advantage in technical domains, evidenced by its higher coding index of 57.2 compared to Claude’s 52.5. This lead is mirrored in specific benchmarks like TerminalBench Hard (0.576 vs 0.515) and SciCode (0.566 vs 0.545), suggesting that OpenAI’s model is better optimized for software engineering and scientific reasoning tasks.

Conversely, Claude Opus 4.7 edges out GPT-5.4 in general intelligence, scoring 57.3 against GPT-5.4’s 56.8. Claude also demonstrates superior performance on the TAU2 benchmark (0.886 vs 0.871), indicating a more robust capacity for complex, multi-step reasoning. While both models show high proficiency in GPQA—with GPT-5.4 at 0.92 and Claude at 0.914—the data suggests that GPT-5.4 is the more specialized tool for code-heavy environments, while Claude maintains a slight advantage in broader, adaptive reasoning scenarios.

Speed and Cost

Operational efficiency is where these two models diverge most sharply. GPT-5.4 (xhigh) is significantly more cost-effective, with a blended price of $5.63 per million tokens, less than half the $10.94 blended cost of Claude Opus 4.7. Furthermore, GPT-5.4 delivers a higher output speed of 78.88 tokens per second, making it better suited for long-form content generation or large-scale data processing.

However, the user experience regarding latency is inverted. Claude Opus 4.7 features a time-to-first-token of 21.112 seconds, which is substantially faster than the 186.304 seconds required by GPT-5.4. For interactive applications where the user expects an immediate start to the response, Claude’s performance is vastly superior. GPT-5.4’s slow initial response time may prove disruptive in conversational interfaces, even if its sustained throughput is higher.

Which model fits which workflow

Choosing between these models requires balancing the need for technical precision against the need for interactive responsiveness. GPT-5.4 (xhigh) is best positioned for backend automation, code generation, and batch processing where cost-per-token and sustained throughput are the primary metrics of success. The higher coding index and lower price point make it a logical choice for developers integrating AI into software pipelines.

Claude Opus 4.7 (Adaptive Reasoning, Max Effort) is better suited for high-stakes, interactive reasoning tasks. Its ability to begin generating responses nearly nine times faster than GPT-5.4 makes it the preferred choice for customer-facing applications or real-time research assistance where the user’s time is a premium. While it comes at a higher cost, the trade-off is a more fluid, responsive interaction that feels less like a batch process and more like a real-time dialogue.

Decision takeaway

Ultimately, the choice depends on the specific constraints of your project. If your workflow is dominated by coding tasks and you are operating at scale, the economic and technical advantages of GPT-5.4 are difficult to ignore. If your primary goal is to provide a seamless, responsive experience for human users who need complex reasoning on demand, Claude Opus 4.7 remains the more agile and capable option despite the higher price tag.