GPT-5.4 is a frontier large language model released by OpenAI on March 5, 2026. It serves as a unified flagship model that consolidates the capabilities of previous specialized versions, including the coding-centric GPT-5.3-Codex and the reasoning-focused GPT-5.2 series. In its non-reasoning configuration—the default state when reasoning effort is set to "none"—the model functions as a high-performance, general-purpose engine optimized for professional workflows, text generation, and rapid tool execution without the latency of extended internal chain-of-thought processing.
Key Capabilities and Performance
The model is characterized by a significantly expanded 1,050,000-token context window, enabling the analysis of massive datasets such as entire legal discovery archives or enterprise-scale software repositories in a single request. GPT-5.4 is notable for being the first mainline OpenAI model to integrate native computer-use capabilities, which allows it to navigate desktop environments and interact directly with software interfaces. In technical evaluations, it demonstrates a 33% reduction in factual errors compared to its predecessors and maintains accuracy across the full extent of its million-token context.
Architectural Features and Prompting
GPT-5.4 introduces an intelligent tool search mechanism that reduces token consumption by approximately 47% in tool-heavy agentic workflows by retrieving tool definitions on demand. It also supports Mid-Response Steering, a feature allowing users to interrupt and redirect the model's logic during output generation. The model features a knowledge cutoff of August 31, 2025, and supports multimodal inputs, excelling in image perception for UI design and complex spreadsheet analysis.
To optimize GPT-5.4 performance, OpenAI recommends using explicit "output contracts" and clearly defined completion criteria. The model is particularly effective when used with modular, block-structured prompts that provide grounded citations for evidence-rich synthesis. For tasks requiring lower latency, the model can also be deployed in a specialized "Fast Mode" that streamlines internal analysis steps for near-instant responses.