Introducing GPT-5.4

Introducing GPT-5.4 | OpenAI

March 5, 2026

Introducing GPT‑5.4

Designed for professional work

Loading…

Share

Today, we’re releasing GPT‑5.4 in ChatGPT (as GPT‑5.4 Thinking), the API, and Codex. It’s our most capable and efficient frontier model for professional work. We’re also releasing GPT‑5.4 Pro in ChatGPT and the API, for people who want maximum performance on complex tasks.

GPT‑5.4 brings together the best of our recent advances in reasoning, coding, and agentic workflows into a single frontier model. It incorporates the industry-leading coding capabilities of GPT‑5.3‑Codex⁠ while improving how the model works across tools, software environments, and professional tasks involving spreadsheets, presentations, and documents. The result is a model that gets complex real work done accurately, effectively, and efficiently—delivering what you asked for with less back and forth.

In ChatGPT, GPT‑5.4 Thinking can now provide an upfront plan of its thinking, so you can adjust course mid-response while it’s working, and arrive at a final output that’s more closely aligned with what you need without additional turns. GPT‑5.4 Thinking also improves deep web research, particularly for highly specific queries, while better maintaining context for questions that require longer thinking. Together, these improvements mean higher-quality answers that arrive faster and stay relevant to the task at hand.

In Codex and the API, GPT‑5.4 is the first general-purpose model we’ve released with native, state-of-the-art computer-use capabilities, enabling agents to operate computers and carry out complex workflows across applications. It supports up to 1M tokens of context, allowing agents to plan, execute, and verify tasks across long horizons. GPT‑5.4 also improves how models work across large ecosystems of tools and connectors with tool search, helping agents find and use the right tools more efficiently without sacrificing intelligence. Finally, GPT‑5.4 is our most token efficient reasoning model yet, using significantly fewer tokens to solve problems when compared to GPT‑5.2—translating to reduced token usage and faster speeds.

Together with advances in general reasoning, coding, and professional knowledge work, GPT‑5.4 enables more reliable agents, faster developer workflows, and higher-quality outputs across ChatGPT, the API, and Codex.

GPT‑5.4

GPT‑5.3‑Codex

GPT‑5.2

GDPval (wins or ties)

83.0%

70.9%

70.9%

SWE-Bench Pro (Public)

57.7%

56.8%

55.6%

OSWorld-Verified

75.0%

74.0%*

47.3%

Toolathlon

54.6%

51.9%

46.3%

BrowseComp

82.7%

77.3%

65.8%

*Previously reported as 64.7%. GPT‑5.3‑Codex achieves 74.0% with a newly introduced API parameter that preserves the original image resolution.

Knowledge work

Building on GPT‑5.2’s general reasoning capabilities, GPT‑5.4 delivers even more consistent and polished results on real-world tasks that matter to professionals.

On GDPval⁠, which tests agents’ abilities to produce well-specified knowledge work across 44 occupations, GPT‑5.4 achieves a new state of the art, matching or exceeding industry professionals in 83.0% of comparisons, compared to 70.9% for GPT‑5.2.

In GDPval, models attempt well-specified knowledge work spanning 44 occupations from the top 9 industries contributing to U.S. GDP. Tasks request real work products, such as sales presentations, accounting spreadsheets, urgent care schedules, manufacturing diagrams, or short videos. Reasoning effort was set to xhigh for GPT‑5.4 and heavy for GPT‑5.2 (a slightly lower level in ChatGPT).

> “GPT-5.4 is the best model we’ve ever tried. It’s now top of the leaderboard on our APEX-Agents benchmark, which measures model performance for professional services work. It excels at creating long-horizon deliverables such as slide decks, financial models, and legal analysis, delivering top performance while running faster and at a lower cost than competitive frontier models.”

— Brendan Foody, CEO at Mercor

We put a particular focus on improving GPT‑5.4’s ability to create and edit spreadsheets, presentations, and documents. On an internal benchmark of spreadsheet modeling tasks that a junior investment banking analyst might do, GPT‑5.4 achieves a mean score of 87.3%, compared to 68.4% for GPT‑5.2. On a set of presentation evaluation prompts, human raters preferred presentations from GPT‑5.4 68.0% of the time over those from GPT‑5.2 due to stronger aesthetics, greater visual variety, and more effective use of image generation.

Documents were generated with reasoning effort set to xhigh

You can try these capabilities in ChatGPT using GPT‑5.4 Thinking or Pro. If you’re an Enterprise customer, we recommend using our newly released ChatGPT for Excel add-in⁠, which was also launched today. We've also updated our spreadsheet⁠ and presentation skills⁠ available in Codex and the API.

To make GPT‑5.4 better at real-world work, we continued our progress at driving down hallucinations and errors. GPT‑5.4 is our most factual model yet: on a set of de-identified prompts where users flagged factual errors, GPT‑5.4’s individual claims are 33% less likely to be false and its full responses are 18% less likely to contain any errors, relative to GPT‑5.2.

> “GPT-5.4 sets a new bar for document-heavy legal work. On our BigLaw Bench eval, it scored 91%. Compared to other models, GPT-5.4 is currently better at structuring complex transactional analysis, maintaining accuracy across lengthy contracts, and delivering the high level of detail legal practitioners require.”

— Niko Grupen, Head of Applied Research at Harvey

Computer use and vision

GPT‑5.4 is our first general-purpose model with native computer-use capabilities and marks a major step forward for developers and agents alike. It’s the best model currently available for developers building agents that complete real tasks across websites and software systems.

We’ve designed GPT‑5.4 to be performant across a wide range of computer-use workloads. It is excellent at writing code to operate computers via libraries like Playwright, as well as issuing mouse and keyboard commands in response to screenshots. Its behavior is steerable via developer messages, meaning that developers can adjust behavior to suit particular use cases. Developers can even configure the model’s safety behavior to suit different levels of risk tolerance by specifying custom confirmation policies.

The model’s performance and flexibility are reflected across…