OpenAI Awards Million-Dollar Bonuses to Employees

OpenAI has announced significant bonus payouts for about 1,000 of its employees—roughly one-third of its full-time workforce—as it prepares to launch its latest AI model, GPT-5.

On the eve of the launch, OpenAI CEO Sam Altman surprised staff with a message on Slack, revealing that researchers and software engineers working in applied engineering, scaling, and safety will receive quarterly bonuses over the next two years. According to The Verge, the bonuses vary by role and seniority, with top researchers expected to earn mid-single-digit millions, while engineers will receive bonuses in the hundreds of thousands. Employees can choose to receive their bonuses in stock, cash, or a combination of both.

Altman attributed the increased compensation to current market dynamics, highlighting the fierce competition for AI talent. “As we mentioned a few weeks ago, we have been looking at compensation for our technical teams given the movement in the market,” Altman stated. “We very much intend to keep increasing comp as we keep doing better and better as a company. But we wanted to be transparent about this one since it’s a new thing for us.”

The competition for AI experts is heating up across Silicon Valley, with tech giants and startups alike announcing bonuses to attract and retain top talent. Altman recently lost several key researchers to Meta, and Elon Musk’s xAI is also actively recruiting.

India remains OpenAI’s second-largest market after the US and is poised to become its largest market soon, according to Altman.

The newly launched GPT-5 is now available to all users. Plus subscribers get extended usage, while Pro subscribers gain access to GPT-5 Pro — an advanced version with deeper reasoning capabilities for more complex queries. The company describes GPT-5 as “a unified system with a smart, efficient model that answers most questions, a deeper reasoning model (‘GPT-5 thinking’) for harder problems, and a real-time router that quickly decides which to use based on conversation type, complexity, tool needs, and user intent.”