The company released the model, GPT-5.4, Thursday (March 5) in ChatGPT (as GPT-5.4 Thinking), the API and Codex. It also released GPT-5.4 Pro in ChatGPT and the API for users seeking “maximum performance on complex tasks,” OpenAI said in a Thursday press release.
GPT-5.4 includes the coding capabilities of GPT-5.3-Codex as well as improvements in working across tools, software environments, and tasks that involve spreadsheets, presentations and documents, according to the release.
GPT-5.4 Thinking improves deep web research, better maintains context, and provides users with an upfront plan of its thinking so they can adjust course while it’s working, the release said.
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In the API and Codex, GPT-5.4 has computer-use capabilities, supports up to 1 million tokens of context, helps agents find the right tools, and is OpenAI’s most token-efficient reasoning model yet, per the release.
In a test of its ability to produce knowledge work across 44 occupations, GPT-5.4 matches or exceeds industry professionals in 83% of comparisons, according to the release. The test included tasks such as generating sales presentations, accounting spreadsheets, urgent care schedules, manufacturing diagrams or short videos.
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“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,” OpenAI said in the release.
OpenAI Chief Financial Officer Sarah Friar told CNBC in January that she expects the share of OpenAI’s business that is made up of enterprise customers to increase from the current 40% to 50% by the end of the year.
In February, OpenAI announced that it now offers both a platform and the services of human engineers to help enterprises use AI agents. The new platform, Frontier, helps enterprises build, deploy and manage AI agents.
During the same month, OpenAI said it is collaborating with four consulting firms to help it deploy Frontier and help customers that adopt the enterprise platform “define strategy, integrate systems, redesign workflows, and scale deployment globally.”
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