1. **Analyze the Request:** * **Role:** News summarization expert. * **Task:** Summarize the provided article. * **Constraints:** * Concisely (2-4 sentences). * Focus on the most important info. * NO copy-pasting. * NO simple restatement of the title. * Add new info beyond the title. * Answer in English. 2. **Analyze the Input:** * **Title:** "GPT-5.4 Thinking System Card" * **Source:** "hackernews" * **Article Text:** "GPT-5.4 Thinking System Card" followed by "Summary:" and then... nothing. 3. **Identify the Problem:** The user provided a title but *no actual article content*. The "Article Text" only contains the title repeated and a "Summary:" header. There is literally nothing to summarize. 4. **Determine the Best Course of Action:** * I cannot fulfill the request to summarize the *content* because the content is missing. * I need to inform the user that the text is missing. * However, sometimes in these prompts, there might be a hidden instruction or a misunderstanding of the input format. But looking at the raw text provided: `Article Text: GPT-5.4 Thinking System Card \n\n Summary:`, it is definitively empty. 5. **Formulate the Response:** * *Draft 1:* I can't summarize this because there is no article text. * *Draft 2 (Better):* Please provide the full text of the article. You only included the title. * *Draft 3 (Addressing the specific constraints):* Since I am simulating a response based on the *potential* existence
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[Skip to main content](https://openai.com/index/introducing-gpt-5-4/#main) [](https://openai.com/) * [Research](https://openai.com/research/index/) * Products * [Business](https://openai.com/business/) * [Developers](https://openai.com/api/) * [Company](https://openai.com/about/) * [Foundation(opens in a new window)](https://openaifoundation.org) [Try ChatGPT(opens in a new window)](https://chatgpt.com/?openaicom-did=709e7f96-28e4-431d-8252-3e4d75616b57&openaicom_referred=true) * Research * Products * Business * Developers * Company * [Foundation(opens in a new window)](https://openaifoundation.org) Introducing GPT-5.4 | OpenAI Table of contents * [Knowledge work](https://openai.com/index/introducing-gpt-5-4/#knowledge-work) * [Computer use and vision](https://openai.com/index/introducing-gpt-5-4/#computer-use-and-vision) * [Coding](https://openai.com/index/introducing-gpt-5-4/#coding) * [Tool use](https://openai.com/index/introducing-gpt-5-4/#tool-use) * [Steerability](https://openai.com/index/introducing-gpt-5-4/#steerability) * [Safety](https://openai.com/index/introducing-gpt-5-4/#safety) * [Availability and pricing](https://openai.com/index/introducing-gpt-5-4/#availability-and-pricing) * [Evaluations](https://openai.com/index/introducing-gpt-5-4/#evaluations) March 5, 2026 [Product](https://openai.com/news/product-releases/)[Release](https://openai.com/research/index/release/) # Introducing GPT‑5.4 Designed for professional work Loading… 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](https://openai.com/index/introducing-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](https://openai.com/index/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 diagr