OpenAI: GPT-5.2 Pro

The practical problem this model removes is the fragility that appears on the hardest, longest tasks, where lesser models drift, drop context, or fumble a chain of steps. Presented as OpenAI's most advanced model, GPT-5.2 Pro improves on GPT-5 Pro specifically in agentic coding and long-context performance, so its intended user is someone running an extended, high-stakes job, such as an autonomous agent working through a large specification and a sprawling codebase without losing the thread partway. It offers a 400,000-token context window bigger than most models listed here, image input, chain-of-thought reasoning, tool and function calling, and structured JSON output. Relative to alternatives such as Claude Sonnet 5 or Gemini, the pitch is maximum reliability on demanding, long-running work rather than economy. That reliability is expensive: pricing is above average at 21 dollars per million input tokens, the steepest in this batch, with no free tier. Ideal for teams whose workloads are genuinely long-context and agentic, where a failure mid-run costs more than the premium token price. Reserve it for those top-end tasks; for routine research, writing, or high-volume calls, a mini, nano, or standard variant delivers most of the value at a small fraction of the cost.