GPT-5.4 Pro

What is GPT-5.4 Pro?

GPT-5.4 Pro is the highest-compute variant in the GPT-5.4 family. OpenAI positions it as the model to choose when you need maximum reasoning depth and precision, even if it costs more and runs more slowly. It is built for the hardest professional and scientific tasks, where the cost of an error is high and higher compute can materially improve outcomes.

Compared to GPT-5.4, the Pro version focuses on quality over speed. It is only available via the Responses API and is intended for deep, compute-intensive reasoning. OpenAI notes that GPT-5.4 Pro may take minutes to complete complex tasks and recommends background mode for most requests. The result is a model designed for deep reasoning and structured analysis rather than fast, interactive chat.

Official model ID, context window, and limits

GPT-5.4 Pro uses the model ID `gpt-5.4-pro`. OpenAI documents a 1,050,000 token context window and 128,000 maximum output tokens, matching the base GPT-5.4 model. It accepts text and image inputs and produces text outputs only.

Reasoning effort and compute profile

GPT-5.4 Pro does not include the lowest reasoning effort modes. According to the model documentation, it only supports medium, high, and xhigh. This reflects its positioning: it is intended for deep reasoning, not quick low-cost responses. If you need fast or low latency output, GPT-5.4 or GPT-5.3 Chat are better fits.

The model’s higher compute makes it especially effective for tasks with complex constraints, such as multi-criteria optimization, rigorous technical analysis, or long-form structured writing that requires consistent logic across many sections.

Tooling support and API availability

GPT-5.4 Pro is available only in the Responses API. The model page lists support for the Responses endpoint and does not include Chat Completions, Realtime, or Assistants. This is an important distinction: GPT-5.4 Pro is optimized for deep reasoning rather than broad interactive chat usage.

GPT-5.4 Pro accepts text and image inputs and produces text output only. Audio, image, or video outputs are not supported. If your workflow needs multimodal outputs or real-time interaction, GPT-5.4 (non-Pro) is typically a better fit.

Quality positioning and benchmark signals

OpenAI describes GPT-5.4 Pro as a higher-compute variant of GPT-5.4 with improved reasoning reliability. While the public model page does not list benchmark scores, the GPT-5.4 release highlights strong results across coding, reasoning, and multimodal evaluations. GPT-5.4 Pro is intended to push those results further for difficult tasks where additional compute leads to better outcomes.

In practical terms, you should expect fewer constraint violations, better long-chain logic, and improved consistency across multi-section deliverables. The model is best treated as an “accuracy-first” option rather than a general default.

Pricing snapshot and long-context costs

OpenAI lists GPT-5.4 Pro at $30 per 1M input tokens, $3 per 1M cached input tokens, and $180 per 1M output tokens. For prompts above 272K input tokens, the model uses a higher pricing tier (2x input and 1.5x output) for the entire session. This means very long prompts can become significantly more expensive compared to standard-length requests.

The higher pricing reflects the additional compute used by the Pro model. For cost-sensitive production systems, it is usually best to reserve GPT-5.4 Pro for the most demanding steps and use GPT-5.4 or GPT-5.3 Chat for routine tasks.

Long-context strategy

GPT-5.4 Pro supports the same 1.05M token context window as GPT-5.4. This is powerful for large-scale analysis but can be expensive. A practical approach is to use GPT-5.4 for ingestion and summarization, then pass condensed context to GPT-5.4 Pro for final reasoning or decision steps. This reduces cost while still leveraging the Pro model for the most critical reasoning work.

If you do need a full long-context run, structure the prompt with clear headings and explicit instructions for how to interpret each section. This improves consistency and reduces the risk of the model focusing on the wrong parts of the context.

When is GPT-5.4 Pro worth it?

GPT-5.4 Pro is worth the premium when failures are costly or when tasks are so complex that lower-compute models frequently miss constraints. Examples include high-stakes legal analysis, rigorous financial modeling, safety-sensitive engineering reviews, and mission-critical research synthesis. In these cases, even small improvements in reasoning reliability can justify the cost.

If your workflow involves many quick tasks (summaries, short drafts, chat responses), the Pro model is usually not justified. The base GPT-5.4 model provides a better balance of cost, speed, and capability. Treat GPT-5.4 Pro as a precision tool rather than a general default.

High-value use cases

GPT-5.4 Pro is most valuable when the output is directly tied to high-stakes outcomes. This includes regulatory analysis, complex financial modeling, security-sensitive reasoning, deep scientific synthesis, and technical policy interpretation. In these settings, small improvements in correctness can outweigh the higher cost.

Another common use case is expert report drafting. The model can generate structured arguments, compare options, and produce long-form writing with consistent logic. It is especially helpful when a single analysis must remain coherent across dozens of pages.

Comparison: GPT-5.4 Pro vs GPT-5.4

The table below summarizes the most important differences. The core architecture is similar, but GPT-5.4 Pro emphasizes depth and reliability, while GPT-5.4 emphasizes speed, lower cost, and broader endpoint availability.

Choosing between GPT-5.4 Pro and GPT-5.3-Codex

GPT-5.3-Codex is a specialized coding agent that excels in software engineering workflows and tool-driven coding tasks. GPT-5.4 Pro, by contrast, is a general reasoning model. If your task is primarily code-centric and requires multi-file changes, tests, and tooling, GPT-5.3-Codex is often more efficient. If the task is broader, such as research synthesis with technical conclusions or cross-domain reasoning, GPT-5.4 Pro is the better choice.

A hybrid workflow can also work well: use GPT-5.4 Pro to define the architecture or reasoning-heavy plan, then hand the execution to GPT-5.3-Codex for coding and testing.

Prompting and workflow guidance

GPT-5.4 Pro responds well to detailed, structured prompts that define explicit constraints and evaluation criteria. For example, if you are requesting a legal analysis, specify the jurisdiction, the relevant standards, and the format of the output. If you are asking for a technical report, define the audience and the expected sections. The model's depth is most valuable when it has clear boundaries.

Because Pro is more expensive, use it strategically. A common pattern is to run a cheaper model for initial drafts, then use GPT-5.4 Pro to refine the final answer or validate a high-risk decision. This provides a good balance of cost and reliability.

Quality assurance checklist

When you use GPT-5.4 Pro for critical output, treat it like a high-value expert review. A simple checklist can improve reliability: verify that the output matches all constraints, confirm that numerical calculations are consistent, and check that any stated assumptions are acceptable. If a response contains multiple recommendations, ask the model to restate them in a concise list to make verification easier.

If the output is used for decisions, add a brief counterargument step and ask the model to surface potential failure modes. This often reveals edge cases that a single pass would miss, and it can significantly improve decision quality in high-stakes contexts.

For legal or compliance tasks, request explicit citations to the relevant sections of the provided context. For analytical tasks, ask for a short sanity-check step that reviews the main conclusion. This adds a few extra tokens but can prevent costly errors when decisions depend on the result.

Limitations and tradeoffs

The main tradeoff of GPT-5.4 Pro is speed and cost. It is slower than GPT-5.4 and lacks several tool integrations, which can limit automation use cases. If you need broad tool coverage or fast response times, the Pro model is not ideal.

As with all models, GPT-5.4 Pro can still make mistakes. It is more reliable, but it does not guarantee correctness. For critical outputs, integrate verification steps or expert review into your workflow.

Enterprise and safety considerations

The model documentation lists support for zero data retention and data residency options, and the pricing documentation notes a 10% uplift when data residency is enabled. If you are deploying GPT-5.4 Pro in regulated environments, confirm the data handling configuration and plan for the pricing uplift.

As with any advanced model, outputs should be reviewed in high-stakes contexts. GPT-5.4 Pro improves reliability but does not guarantee correctness. For safety-sensitive decisions, combine model output with human oversight or automated verification.

Multimodal input use cases

GPT-5.4 Pro accepts image inputs, which makes it useful for document analysis, diagram interpretation, and UI reasoning. If you are analyzing images, provide a short textual instruction describing the task, such as “extract the table values,” “summarize this chart,” or “identify the risks in this architecture diagram.” This helps the model focus on the right aspects of the image.

For complex visual tasks, consider setting reasoning effort to high or xhigh to improve accuracy. This is particularly important when the image contains dense information, such as financial statements or compliance documents.