Deep research successfully completed 26.6% of the recently developed test, which consists of over 3,000 questions across hundreds of subjects ranging from rocket science to analytic philosophy. Powered by OpenAI’s frontier o3 model, the AI agent can synthesize a wide range of information and complete multistep research within five-to-30 minutes, its creators say.

OpenAI’s o1 and DeepSeek’s R1 models, which previously sat atop the leaderboard, could only get through roughly 9% of the exam, meaning OpenAI’s new agent represents a nearly threefold jump in performance. The company said the largest gains appeared on inquiries related to chemistry, humanities and social sciences, and mathematics.

Frank Downing, a director of research at Cathie Wood’s ARK Invest, noted that OpenAI’s new agent also set a new state-of-the-art score on GAIA, a test for AI assistants that poses real-world questions that are conceptually simple for humans, but challenging for most digital agents. The new offering provides deeper research and analysis, he added, compared with a competing product launched by Google in December.

But all those accomplishments could look miniscule, Downing said, if subsequent models from OpenAI and competitors make progress on solving Humanity’s Last Exam at a pace similar to how weaker AI models conquered previous academic benchmarks.  

“Humanity’s Last Exam could be saturated within the next 12 months,” he wrote in a note Monday, “effectively surpassing expert-level technical knowledge and reasoning capability.”

What is Humanity’s Last Exam?

The test is the result of an effort led by Dan Hendrycks, the director of the Center for AI Safety and an advisor for companies such as Scale AI and Elon Musk’s xAI. He previously had created another exam called Massive Multitask Language Understanding, or MMLU, which cutting-edge versions of Anthropic’s Claude, Meta’s Llama, and OpenAI’s Chat GPT have been able to mostly crack as of late last year.

Hendrycks said he was inspired to create Humanity’s Last Exam after a conversation with Musk about existing AI tests being too easy.

“Elon looked at the MMLU questions and said, ‘These are undergrad level. I want things that a world-class expert could do,’” Hendrycks told the New York Times in January.

So Hendrycks, with support from Scale AI, spearheaded a project designed to serve as “the final closed-ended academic benchmark of its kind with broad subject coverage.” His team compiled questions submitted by hundreds of college professors, prize-winning mathematicians, and other experts in their fields.

“[The exam] emphasizes world-class mathematics problems aimed at testing deep reasoning skills broadly applicable across multiple academic areas,” the team wrote in a paper debuting the test in January.

Once models start scoring over 50%, Hendrycks said, it’s safe to say humans have met their match in this regard. After that, the clock is presumably ticking until the world witnesses what is termed artificial general intelligence, or the ability of a machine to possess all the cognitive abilities of humans. OpenAI says it envisions this technology, commonly dubbed AGI, as being capable of producing novel scientific research.

“We are now confident we know how to build AGI as we have traditionally understood it,” OpenAI CEO Sam Altman said in a blog post in January.

On Sunday, Google DeepMind CEO Demis Hassabis said it could arrive in just five years.

“And I think society needs to get ready for that and what implications that will have,” he said in Paris on Sunday ahead of the AI Action Summit hosted by the city, CNBC reported.

On that front, time seems to be of the essence.