GPT-5.2 vs. GPT-5.5: Evaluating OpenAI’s High-Performance Iteration

What the benchmarks show

The progression from GPT-5.2 to GPT-5.5 reflects OpenAI's strategic pivot toward higher-order reasoning and technical execution. GPT-5.5 (xhigh) demonstrates a notable increase in its Intelligence index, rising from 51.3 to 60.2, and a significant boost in its Coding index, moving from 48.7 to 59.1. These gains are validated by performance improvements in specialized benchmarks; for instance, GPT-5.5 achieves a TAU2 score of 0.938 compared to GPT-5.2’s 0.847, and a TerminalBench Hard score of 0.606 versus 0.469.

However, the trade-off is a lack of data regarding the newer model's mathematical capabilities. While GPT-5.2 boasts an exceptional Math index of 99 and an AIME 2025 score of 0.99, these metrics are currently unknown for GPT-5.5. Users who rely heavily on high-level mathematical proofs or specific quantitative modeling may find the established performance of GPT-5.2 more predictable, whereas those prioritizing complex software development and multi-step reasoning tasks will likely benefit from the architectural refinements present in GPT-5.5.

Speed and cost

Operational efficiency presents a complex trade-off between the two models. GPT-5.5 is significantly more expensive, with a blended cost of $11.25 per million tokens, more than double the $4.81 per million tokens required for GPT-5.2. This pricing structure reflects the increased computational resources required to support the newer model's enhanced reasoning capabilities.

In terms of raw speed, the models are remarkably similar in output generation, with GPT-5.2 producing 68.412 tokens per second and GPT-5.5 producing 68.227 tokens per second. The most distinct performance difference lies in the time to first token; GPT-5.5 offers a faster response initiation at 47.763 seconds, compared to the 68.593 seconds required by GPT-5.2. This reduction in latency makes GPT-5.5 feel more responsive in interactive environments, even if the sustained output speed remains consistent across both versions.

Which model fits which workflow

Choosing between these models depends on the specific demands of the user's workflow. GPT-5.2 is best suited for cost-sensitive applications and projects where mathematical precision is the primary requirement. Its proven track record in math-intensive benchmarks suggests it remains a reliable engine for scientific research and quantitative analysis where budget constraints are a factor.

Conversely, GPT-5.5 is optimized for high-stakes technical environments. Its superior performance in TerminalBench Hard and HLE benchmarks indicates that it is better equipped to handle complex, multi-step coding tasks and system-level interactions. For developers and engineers working on intricate software architectures, the higher cost of GPT-5.5 is likely offset by the reduction in manual debugging and the increased accuracy in complex reasoning tasks.

Decision takeaway

Ultimately, the choice between GPT-5.2 and GPT-5.5 is a decision between specialized mathematical reliability and general-purpose technical advancement. GPT-5.2 remains a powerful, cost-effective tool for specific quantitative domains. GPT-5.5, while carrying a premium price tag, provides a more responsive and capable environment for the rigors of modern software engineering and complex reasoning. Users should prioritize their specific needs—whether that is budget efficiency and math performance or coding accuracy and reduced latency—to select the model that aligns with their operational goals.