GPT-5.5

What you need to know

GPT-5.5 distinguishes itself through strict adherence to constraints and instruction fidelity rather than expansive reasoning breadth. It achieves perfect internal scores for constrained rewriting, faithfulness, and long-context processing, which translates to reliable performance when working with extensive documents or rigid formatting requirements. The 1.1M token context window supports processing large codebases or research corpora in a single pass, and the 100% score on AIME 2025 indicates mathematical and logical reasoning remains robust even at scale. This makes the model particularly effective for workflows that demand exact compliance over exploratory generation.

At $5.00/MTok input and $30.00/MTok output, the blended cost sits at $23.75/MTok, placing it firmly in the premium pricing tier. The #11 overall rank among 71 evaluated models reflects this trade-off: you are paying for consistency and capacity rather than absolute top-tier performance across every category. The 80.6% score on SWE-bench Verified confirms strong software engineering capabilities, but the 4/5 internal ratings for structured output, strategic analysis, and creative problem solving show measurable gaps when tasks require open-ended ideation or complex multi-step planning. The pricing is justified for pipelines that prioritize deterministic outputs and long-context retention, but less efficient for high-volume exploration or highly structured data formatting where mid-tier alternatives perform comparably.

Use this if your workload requires processing documents beyond standard context limits, enforcing strict output constraints, or maintaining high faithfulness to source material. It is also a practical fit for tabular data extraction and agentic tool-calling workflows that need predictable behavior. Skip this if your primary use case involves open-ended creative generation, complex strategic analysis, or high-throughput structured data formatting where the premium output cost does not align with the performance delta. The 4/5 scores in those areas indicate capable but not exceptional results, making lower-cost models a more efficient choice for those specific tasks.

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