GPT 5.4 — Frontier Reasoning, Coding, and Multimodal Language Model
What is GPT-5.4?
GPT-5.4 is OpenAI's latest flagship large language model, released March 5, 2026. It is the first mainline reasoning model to incorporate the frontier coding capabilities of GPT-5.3-Codex, combining state-of-the-art reasoning, vision, and software engineering into a single unified model. Developers and teams access it via API to build production-grade assistants, autonomous agents, and intelligent workflows.
Beyond text generation, GPT-5.4 introduces native computer-use capabilities — enabling agents to autonomously operate applications, navigate interfaces, and execute complex multi-step workflows without human intervention. It supports a 1 million token context window, making it uniquely suited for long-horizon tasks where the model must plan, execute, and verify work across massive amounts of context.
On GDPval — a benchmark measuring AI performance across 44 professional occupations — GPT-5.4 achieves 83.0% match with industry professionals, up from 70.9% for GPT-5.2, the largest single-generation gain in the series.
Key Features
- •1M Token Context Window — Process entire codebases, legal documents, or research corpora in a single call.
- •Native Computer Use — The first general-purpose model with built-in computer-use: agents can click, type, and navigate applications autonomously.
- •Frontier Coding (GPT-5.3-Codex Level) — Generate production-quality code, handle multi-file changes, follow repo-specific patterns, and debug with minimal retries.
- •Tool Search — Intelligently selects the right tools from large ecosystems, eliminating manual tool-list maintenance in system prompts.
- •High-Resolution Vision — Accepts images with 10M+ pixels without compression, enabling precise analysis of diagrams, schematics, and UI screenshots.
- •Multimodal Inputs — Accepts both text prompts and images in a single request, with context-aware fusion of both modalities.
- •Token Efficiency — Significantly fewer tokens to solve problems compared to GPT-5.2 — faster and more cost-effective for equivalent task complexity.
Best Use Cases
Software Engineering and Code Generation — GPT-5.4 excels at generating, reviewing, and refactoring production code. It handles multi-file diffs, understands repo-specific conventions, and integrates the full Codex-level capability into its general reasoning loop. Teams report needing fewer prompt-engineering cycles to get correct outputs.
Agentic Workflows — With native computer use and tool search, GPT-5.4 is the default choice for building autonomous agents that operate over long task horizons. It reduces end-to-end time on multi-step trajectories and completes tasks with fewer intermediate tool calls.
Document Intelligence and Research — The 1M token window allows processing of entire books, contracts, or technical specifications. Pair this with structured output support for high-fidelity extraction and synthesis.
Visual Analysis — Analyze high-resolution diagrams, architecture charts, medical images, UI screenshots, and handwritten documents without lossy compression degrading results.
Enterprise Knowledge Work — On GDPval, GPT-5.4 matches or exceeds professional-level output across occupations including legal, financial analysis, software engineering, and scientific research.
Weaknesses — GPT-5.4 at xhigh reasoning effort incurs significant latency and token cost. For high-volume, latency-sensitive tasks, GPT-5.4 mini or nano are better fits.
Prompt Tips and Output Quality
GPT-5.4 responds best to prompts that define the output contract explicitly. Specify your expected format, completion criteria, and any constraints upfront rather than letting the model infer them.
Reasoning effort guidance: For most production tasks, the default (none or low) setting is the right starting point. Reserve medium and high for tasks where deeper reasoning clearly improves accuracy. Use xhigh only for long agentic tasks where maximum intelligence outweighs speed and cost considerations.
For coding tasks: Provide the repo context, target language/framework, and a clear description of the change. GPT-5.4 has a strong out-of-the-box coding personality, so over-specifying style constraints is usually unnecessary.
For vision tasks: Upload images at the highest available resolution — GPT-5.4 can now handle 10M+ pixel inputs without compression penalties, so don't downscale before sending.
For agentic workflows: Include explicit grounding instructions — tell the model what tools to prefer, what constitutes task completion, and when to stop and verify. Adding a preamble instruction like Before you call a tool, explain why you are calling it significantly improves tool-calling accuracy.
For long context: Structure your context with clear section headers. GPT-5.4 is optimized for 1M token inputs, but well-organized context consistently yields faster, more accurate outputs.
FAQs
How is GPT-5.4 different from GPT-5.2? GPT-5.4 integrates Codex-level coding, native computer use, tool search, and 1M token context. On GDPval benchmarks, it scores 83.0% vs GPT-5.2's 70.9% — a 12-point professional-match improvement. It also uses significantly fewer tokens per task, reducing API costs.
When should I use GPT-5.4 vs GPT-5.4 mini? Use GPT-5.4 when task quality, reasoning depth, and multi-step accuracy matter most. Use GPT-5.4 mini or nano for high-throughput, latency-sensitive workloads where cost and speed take priority.
Does GPT-5.4 support vision? Yes. GPT-5.4 accepts image inputs alongside text prompts and supports images up to 10M+ pixels. It is especially effective at analyzing complex diagrams, screenshots, and high-resolution documents.
What is tool search, and why does it matter? Tool search allows GPT-5.4 to intelligently identify and select the right tool from a large ecosystem without requiring developers to enumerate every available tool in the system prompt. This reduces prompt size, cost, and maintenance overhead for agent-heavy applications.
What reasoning effort setting should I use? Start at none or low for most tasks. Move to medium or high only when your evaluations show clear accuracy gains. Reserve xhigh for long agentic tasks where maximum intelligence justifies the latency and cost trade-off.
Can GPT-5.4 operate computers autonomously? Yes — GPT-5.4 is the first general-purpose OpenAI model with native computer-use capabilities, available in the API and Codex. It can click, type, navigate UIs, and execute multi-application workflows as part of an agentic pipeline.