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Model details

GPT-5 Pro (OpenAI)

GPT-5 Pro sits within OpenAI's GPT-5 generation as the extended-reasoning variant, purpose-built for complex professional work where sustained analytical depth matters more than fast turnaround. It is positioned for difficult coding, mathematical analysis, scientific questions, and document-heavy research, and it runs at a fixed high reasoning effort rather than offering a developer dial to dial intensity down for simple requests. In practice this makes the model feel less like a general-purpose conversational engine and more like a focused problem-solver that you bring to hard, multi-step questions where reasoning quality is the deciding factor.

Third-party documentation describes a very large context window that comfortably accommodates long documents and image inputs alongside text, paired with a generous maximum output ceiling suitable for detailed explanations and long-form answers. The API snapshot covered by recent guides is identified as gpt-5-pro-2025-10-06, and the model is surfaced through major inference gateways alongside peers such as GPT-5 Image, giving teams a stable endpoint for production workloads. Teams weighing adoption should think of GPT-5 Pro as a premium reasoning specialist: best suited when analytical rigor and the ability to reason across large, mixed text-and-image inputs outweigh cost or latency concerns.

LLM Gatewayopenai/gpt-5-progpt-pro

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LLM Gateway
Model key
openai/gpt-5-pro
Release date
Oct 6, 2025
Last updated
Oct 6, 2025
Knowledge cutoff
2024-09-30
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$15.00
Output token cost
$120.00

Limits

Input tokens
272,000 tokens
Output tokens
272,000 tokens
Context window
400,000 tokens

Transparent token rates

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Rates are shown per one million tokens. Combined means one million input plus one million output tokens.

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Latest news about GPT-5 Pro (OpenAI)

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CoverageAnalysis

An October 31, 2025 arXiv preprint by Adil Salim (arXiv:2510.26647) documents a single-case study of GPT-5-Pro, OpenAI's latest model at the time, acting as a research assistant on a convex analysis problem. Specifically, the paper establishes a Taylor expansion for the gradient of the biconjugation operator — the Fenc Because the evaluation is restricted to one convex-analysis problem and one model, the author explicitly declines to claim generalizable capability claims for GPT-5-pro and positions the main contribution as the documented collaborative reasoning process rather than the mathematical novelty. For an LLM Gateway routing

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