GPT-5.5 Pro

What is GPT-5.5 Pro?

GPT-5.5 Pro is OpenAI's higher-compute version of GPT-5.5. It is designed for difficult problems that benefit from additional reasoning rather than for fast, lightweight conversation. OpenAI positions it for demanding professional work, including complex research, software development, data analysis, document generation, and multi-step workflows involving external tools.

The model uses the GPT-5.5 model line with additional parallel test-time compute. In practical terms, that means it can spend more processing effort evaluating a difficult task before producing an answer. This positioning makes GPT-5.5 Pro an option for cases where a more deliberate response is worth increased latency and token cost. The trade-off is especially important for applications that need immediate responses or process large volumes of requests.

GPT-5.5 Pro is an API model rather than a general description of OpenAI's entire product ecosystem. Its canonical API model ID is gpt-5.5-pro, and the documented snapshot is gpt-5.5-pro-2026-04-23.

Where GPT-5.5 Pro fits in the GPT-5.5 lineup

GPT-5.5 Pro sits at the high-compute end of the GPT-5.5 family. The supplied specifications describe it as the variant intended for the hardest supported tasks, with higher expected quality taking priority over low cost and low latency. The standard GPT-5.5 model is a more relevant alternative when an application does not need the Pro variant's additional computation.

This does not mean GPT-5.5 Pro is automatically the best choice for every request. A faster or less expensive model may be preferable for routine chat, simple extraction, high-volume classification, or interactive applications where users cannot wait several minutes. GPT-5.5 Pro is most defensible when the cost of an incorrect or incomplete result is higher than the cost of additional inference.

Key specifications

The context window is the amount of information the model can consider in a request and its surrounding conversation, subject to the API's request structure and other operational constraints. At 1.05 million tokens, GPT-5.5 Pro is suited to very large document collections, long codebases, extended research material, and workflows that need to retain substantial context. The 128,000-token output ceiling is separate: it limits how much text the model can generate in one response.

The December 1, 2025 knowledge cutoff describes the model's underlying training knowledge. It does not prevent the model from working with newer information supplied through tools such as web search.

Reasoning and answer quality

GPT-5.5 Pro's defining feature is its additional reasoning computation. The model supports medium, high, and xhigh reasoning effort, with high documented as the default. Higher effort can be useful when a task requires comparing alternatives, maintaining consistency across many constraints, checking intermediate conclusions, or planning a multi-step solution.

Examples include synthesizing a large set of research papers, tracing a difficult software defect through several files, reviewing a long technical or financial document, or building an answer that combines web research with calculations and uploaded evidence. These are use cases where a short, plausible answer is less valuable than a carefully checked one.

The supplied research does not provide benchmark scores, so claims about GPT-5.5 Pro's accuracy should be treated as positioning based on OpenAI's documentation rather than as a quantified independent evaluation. Additional reasoning also does not guarantee factual correctness. Important legal, financial, scientific, medical, or operational conclusions still require appropriate human review and verification.

Coding, data analysis, and tool use

GPT-5.5 Pro supports function calling and structured outputs. Function calling lets an application expose defined operations that the model can request, while structured outputs help return data in a prescribed format. These capabilities are useful when the model is part of a larger software workflow rather than only producing free-form prose.

Through the Responses API, the model can use web search, file search, code interpreter, hosted shell, and MCP. Web search can provide current information beyond the model's knowledge cutoff. File search can retrieve relevant passages from an application's indexed files. Code interpreter supports executable analysis, which is useful for calculations, data transformation, and inspecting uploaded material. Hosted shell enables shell-based workflows, while MCP support allows connections to compatible external services.

These tools expand what GPT-5.5 Pro can do, but they do not turn it into an unrestricted autonomous system. Tool permissions, available data, application design, and validation logic remain the responsibility of the developer. Structured output also should not be confused with a guarantee that every generated value is correct.

For coding, the model is suited to advanced implementation, debugging, code review, architecture reasoning, and repository-scale analysis. Its long context can help when many files or extensive technical requirements must be considered together. It does not currently support computer use or apply-patch functionality according to the supplied model documentation, so applications should not assume native interaction with a desktop interface or automatic code modification through those unsupported features.

Supported modalities and unsupported features

GPT-5.5 Pro accepts text and image input and returns text. Image input allows an application to include visual material alongside written instructions, such as diagrams, screenshots, or scanned documents where supported by the surrounding API workflow. The model does not provide image, audio, video, or other direct non-text output.

The documented limitations are significant for product selection. GPT-5.5 Pro does not support audio or video input, audio or video output, streaming, fine-tuning, computer use, apply patch, skills, or tool search. It is therefore a poor fit for real-time voice interfaces, video-processing pipelines, applications that require token streaming, or teams that need to customize model weights through fine-tuning.

It also is not designed around low-latency interaction. OpenAI notes that some requests may take several minutes and recommends background mode where appropriate to reduce timeout risks.

Pricing and API availability

Standard pricing is $30 per 1 million input tokens and $180 per 1 million output tokens. The model has no cached-input discount, so applications should not assume that repeated prompt prefixes will receive the lower cached-input price available for some other model configurations. Regional processing endpoints add a 10 percent uplift.

The pricing difference between input and output is substantial. Long prompts, large document collections, and extensive generated reports can all affect the bill, but output tokens are priced at six times the standard input-token rate. Applications should therefore control unnecessary verbosity, select an appropriate reasoning effort, and avoid sending irrelevant context where possible.

GPT-5.5 Pro is available for Responses API requests and for requests submitted through the Batch API. Batch processing can be useful when immediate results are not required, although the supplied research notes that requests may take substantially longer than ordinary synchronous requests. Background execution is also relevant for workflows that may exceed normal request timeout expectations.

Best use cases

• Complex research and synthesis: comparing many sources, identifying disagreements, and producing a carefully organized conclusion.
• Advanced coding: debugging difficult issues, reviewing large codebases, designing implementations, and reasoning about interactions between components.
• Long-context document analysis: examining contracts, technical specifications, reports, or collections of files that exceed the practical working range of smaller-context models.
• Data analysis: combining uploaded data with executable calculations and written explanations.
• Professional knowledge work: supporting legal, financial, scientific, and technical tasks where accuracy and traceability matter more than instant responses.
• Multi-step tool workflows: combining web search, file retrieval, code execution, hosted shell commands, and external MCP services under application control.

When to choose GPT-5.5 Pro

Choose GPT-5.5 Pro when the task is difficult enough that additional reasoning and a very large context window can materially improve the result. It is particularly appropriate when a human would otherwise need to spend substantial time gathering evidence, checking consistency, performing calculations, or reviewing a complex implementation.

It is less appropriate when the primary requirement is speed, predictable low cost, or real-time interaction. A standard or lower-cost model may be better for simple questions, routine summarization, high-volume processing, short-form extraction, and customer-facing chat where waiting several minutes is unacceptable. A model with streaming, audio, video, fine-tuning, or computer-use support is more suitable when those capabilities are central to the product.

The most practical decision is often to reserve GPT-5.5 Pro for the hardest requests and route simpler work to a faster model. This approach preserves its high-compute reasoning for cases where it is most valuable instead of paying Pro-level pricing for every interaction.

Limitations and final assessment

GPT-5.5 Pro's central trade-off is clear: it prioritizes reasoning depth, context capacity, and complex tool-assisted work over speed and cost. Its $30-per-million input price and $180-per-million output price make it considerably less suitable for economical, high-volume inference than a smaller or faster alternative. Multi-minute requests further limit its usefulness in conversational and real-time settings.

It also has a narrower modality profile than a general multimodal product: image input and text output are supported, but audio and video are not. Streaming, fine-tuning, computer use, and several other documented features are unavailable. For the right workload, however, the combination of a 1.05-million-token context window, 128,000-token output limit, adjustable reasoning effort, structured outputs, function calling, and Responses API tools makes GPT-5.5 Pro a strong fit for demanding professional workflows where careful analysis is more important than rapid or inexpensive responses.