OpenAI cuts inference costs by 50%, launches a price war externally and strictly guards secrets internally.

```

At a crucial juncture where large AI models are shifting from a “technological arms race” to full-on “commercialization,” control over inference costs may already have become the core variable determining a company’s profitability and market pricing power.

According to the latest report by The Information, OpenAI engineers have successfully reduced model inference costs by half. This technological breakthrough will not only greatly improve its longstanding losses caused by computing power consumption, but also provide critical profitability support for its upcoming IPO and a new round of funding amounting to $12 billion.

Since this technology is vital for maintaining a competitive advantage, OpenAI treats it as its “core secret” (secret sauce), even adopting extreme internal confidentiality measures. The company strictly limits the number of employees with knowledge of the technology in order to prevent details from leaking to other AI labs, thereby neutralizing its hard-won cost advantage.

Reporter Steph Palazzolo pointed out in the article: “This is an extremely important core secret for them (secret sauce), they don’t even want to tell other employees inside OpenAI. Because if these things get out, other labs could quickly adopt them and use them to reduce their own costs.”

Inference Costs Slashed: Reshaping Profit Models and Pricing Power

Throughout the commercialization of large AI models, steep inference costs have been a central obstacle to profitability. Previously, due to scarce computing resources and ongoing losses, OpenAI had to completely shut down its video generation tool, Sora, redirecting precious computing resources towards new models and productivity tools that offered clearer business prospects. In this context, the strategic importance of halving inference costs is dramatically magnified.

The sudden drop in costs directly gives OpenAI greater pricing power and profit space in the market. For example, its recently released GPT-5.6 flagship model series, Sol, outperformed Anthropic’s Claude Mythos 5 on the Terminal-Bench 2.1 benchmark, but its pricing is only half that of rival Claude Fable 5. With inference costs reduced, OpenAI is able to launch aggressive “price wars” to capture market share while maintaining healthy gross margins.

For the capital markets, this breakthrough is a key pillar of its valuation logic. OpenAI is nearing completion of a new round of $12 billion financing, with a pre-funding valuation as high as $730 billion, and Sam Altman is actively preparing to complete an IPO ahead of Anthropic. The real reduction in inference costs will directly improve the company's cash flow outlook and provide a financial foundation for its lofty valuation.

The reduction in inference costs also aligns closely with OpenAI’s recent strategic overhaul. Application division CEO Fidji Simo has clearly announced at an all-hands meeting that the company will scale back its multi-pronged approach, marginalize consumer product lines such as Sora, and focus core resources on programming tools and the enterprise market.

Risk Disclaimer and Exemption ClauseThe market carries risks; investments should be made with caution. This article does not constitute personalized investment advice and does not take into account the specific investment objectives, financial situation, or needs of individual users. Users should consider whether any opinions, viewpoints, or conclusions in this article are suitable for their particular circumstances. Investments are made at your own risk. ```