Not a benchmark table. This puts pricing, context, interface fit, and key visibility into one decision card.
当前主推旗舰模型，适合复杂推理、编码、多工具企业工作流。
高阶专业版追踪位，适合企业级重度编码、研究与复杂代理工作流。
This is an internal OpenAI comparison, so the main question is tier, cost, context, and capability rather than provider switching.
On the listed price snapshot, GPT-5.5 is cheaper on combined input and output, but real routing, discounts, and limits still matter.
When context is similar, compare output quality, API stability, limits, and actually callable models first.
Do not start with which model is absolutely stronger. Start with the boundary: cost, context, speed, quality, ecosystem, or supply stability.
If you already hold a key, the valuable check is provider identity, callable models, and whether balance, limits, or subscription status are visible.
Commercially, do not look at model names alone. Combine price, limits, region, upstream stability, and ongoing monitoring.
