# OpenAI Releases GPT-5.4 with Native Computer Use and 1M Token Context

> OpenAI has pushed out GPT-5.4, and the headline claim is that its Thinking variant hits 83 percent on GDPval, the company's benchmark meant to approximate expert-level knowledge work. That figure, if it holds up outside the lab, puts the model in the range of skilled human professionals on the kinds of research, financial analysis, and document-heavy tasks that make up a lot of white-collar jobs. The other upgrades are about range rather than raw reasoning. GPT-5.4 opens up a context window near a million tokens, so it can hold entire codebases or long document sets in view at once, and it ships native computer-use skills for driving spreadsheets, slideshows, and code without a bolt-on agent layer. OpenAI also reports a 33 percent drop in factual errors versus GPT-5.2. What matters here is the direction of travel. Each release quietly moves more of the work from the human writing the prompt to the model executing the task. The benchmark scores are the marketing, but the computer-use and long-context features are the part that will actually change how people use it day to day.

_Section: [Daily AI Updates](https://www.wortins.com/daily-ai) · Source: OpenAI · Published Sunday, September 6, 2026_

## Wortins' read

OpenAI has pushed out GPT-5.4, and the headline claim is that its Thinking variant hits 83 percent on GDPval, the company's benchmark meant to approximate expert-level knowledge work. That figure, if it holds up outside the lab, puts the model in the range of skilled human professionals on the kinds of research, financial analysis, and document-heavy tasks that make up a lot of white-collar jobs. The other upgrades are about range rather than raw reasoning. GPT-5.4 opens up a context window near a million tokens, so it can hold entire codebases or long document sets in view at once, and it ships native computer-use skills for driving spreadsheets, slideshows, and code without a bolt-on agent layer. OpenAI also reports a 33 percent drop in factual errors versus GPT-5.2. What matters here is the direction of travel. Each release quietly moves more of the work from the human writing the prompt to the model executing the task. The benchmark scores are the marketing, but the computer-use and long-context features are the part that will actually change how people use it day to day.

## Source

[Read the full story at OpenAI](https://openai.com/index/introducing-gpt-5-4/)

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